Association between prolactin levels and pregnancy outcomes: evidence from multi-center cohort study and Mendelian randomization analysis

Association between prolactin levels and pregnancy outcomes: evidence from multi-center cohort study and Mendelian randomization analysis | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 13 February 2026 V1 Latest version Share on Association between prolactin levels and pregnancy outcomes: evidence from multi-center cohort study and Mendelian randomization analysis Authors : Yingying Shi , Zhuxian Shi , Yi Chen , Ziyin Ding , Xin Pan , Xiaojing Lin , Shanghui Xie , … Show All … , Xile Cai , Yan Li , Peiyu Wang , Wanyi Xie , Haijie Gao , Xuemei He , Luping Li , Ping Li , Liming Zhou , Haiyan Yang , Zimiao Chen , and Guiquan Wang 0000-0002-6434-1627 [email protected] Show Fewer Authors Info & Affiliations https://doi.org/10.22541/au.177095735.53527870/v1 228 views 79 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Objective To investigate whether moderately elevated serum prolactin levels are associated with pregnancy outcomes. Design Multi-center retrospective cohort study and Mendelian randomization (MR) analysis. Setting Three reproductive centers in Ningbo, Wenzhou, and Xiamen, China. Population 11,004 women undergoing their first in vitro fertilization (IVF) fresh embryo transfer cycle. Individuals with prolactin levels ≥100 ng/mL, missing follow-up outcomes, and relevant diseases were excluded, resulting in 8,073 participants. MR analysis utilized genome-wide association study data from individuals of European ancestry. Methods Multivariable-adjusted logistic regression and combining cohort-specific estimates with meta-analysis were used to examine cohort associations. MR analyses were performed to assess the effect of genetically predicted prolactin levels on pregnancy outcomes and complications. Main Outcome Measures The primary outcome was live birth rate. Secondary outcomes included clinical pregnancy, biochemical pregnancy, miscarriage, preterm birth, and birthweight. Results A total of 8073 individuals were included, with mean age of 32 years, mean body mass index of 22 kg/m 2 , and mean serum prolactin levels of 14.6 ng/mL. Each 5 ng/mL increase in serum prolactin levels were significant associated with increased rate of live birth (odds ratio [OR]= 1.05, 95% confidence interval [CI] = 1.04 – 1.08; P < 0.001), clinical pregnancy (OR = 1.03, 95% CI =1.00–1.06; P = 0.03), biochemical pregnancy (OR = 1.04, 95% CI =1.00–1.07; P = 0.03), and decreased risk of miscarriage (OR =0.92, 95% CI = 0.88–0.97; P = 0.002). However, after adjusting for multiple confounders, the association between prolactin levels and live birth attenuated and became no longer statistically significant (adjusted OR [aOR] 1.03 per 5 ng/mL increase, 95% CI = 0.99–1.06; P = 0.10). Similarly, associations with clinical pregnancy (aOR = 1.02, 95% CI = 0.99–1.05; P = 0.26) and miscarriage (aOR = 0.96, 95% CI = 0.90–1.02; P = 0.14) also became non-significant after adjustment. Consistently, MR analysis indicated that genetically predicted prolactin levels were not significantly associated with live birth, miscarriage, preterm birth, birth weight, gestational diabetes mellitus, maternal hypertensive disorder, preeclampsia ( P > 0.05 for all). Conclusions Moderate increase in serum prolactin levels may not adversely affect pregnancy outcomes. The necessity of treatments for lowering prolactin before conception needs to be re-evaluated. Funding Source: National Natural Science Foundation of China (No. 82401908), Natural Science Foundation of Fujian Province of China (No. 2024J08309) Keywords: Prolactin, Pregnancy outcomes, Cohort study, Multi-centers, Mendelian randomization Title: Association between prolactin levels and pregnancy outcomes: evidence from multi-center cohort study and Mendelian randomization analysis Yingying Shi 1, Ϯ , Zhuxian Shi 1, Ϯ , Yi Chen 2, Ϯ , Ziyin Ding 3, Ϯ , Xin Pan 4, Ϯ , Xiaojing Lin 2, Ϯ , Shanghui Xie 2 , Xile Cai 5 , Yan Li 2 , Peiyu Wang 2 , Wanyi Xie 6 , Haijie Gao 1 , Xuemei He 1 , Luping Li 1 , Ping Li 1 , Liming Zhou 3 , Haiyan Yang 2, * , Zimiao Chen 4, 7, * , Guiquan Wang 1, * 1 Department of Reproductive Medicine, Women and Children’s Hospital, School of Medicine, Xiamen University, Xiamen, China; Xiamen Key Laboratory of Reproduction and Genetics, Xiamen, China. 2 Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. 3 Center for Reproductive Medicine, Women and Children’s Hospital of Ningbo University, Ningbo, China. 4 Cixi Biomedical Research Institute, Wenzhou Medical University, Zhejiang, China. 5 School of Medicine, Zhejiang University, Hangzhou, China. 6 State Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China. 7 Department of Endocrinology and Metabolism, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. Ϯ These authors contributed equally to this study. * These authors are corresponding authors. Contact Information: Guiquan Wang, MD, Department of Reproductive Medicine, Women and Children’s Hospital, School of Medicine, Xiamen University, No. 10 Zhenhai Road, Siming District, Xiamen, China 361003; E-mail: [email protected] ; ORCID: 0000-0002-6434-1627 Zimiao Chen, MD, Department of Endocrinology and Metabolism, The First Affiliated Hospital of Wenzhou Medical University, NanBaiXiang, Ouhai District, Wenzhou, China. Haiyan Yang, MD, Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University, No.96 Fuxuexiang, Lucheng District, Wenzhou, China. Short title PROLACTIN AND PREGNANCY OUTCOMES Objective To investigate whether moderately elevated serum prolactin levels are associated with pregnancy outcomes. Design Multi-center retrospective cohort study and Mendelian randomization (MR) analysis. Setting Three reproductive centers in Ningbo, Wenzhou, and Xiamen, China. Population 11,004 women undergoing their first in vitro fertilization (IVF) fresh embryo transfer cycle. Individuals with prolactin levels ≥100 ng/mL, missing follow-up outcomes, and relevant diseases were excluded, resulting in 8,073 participants. MR analysis utilized genome-wide association study data from individuals of European ancestry. Methods Multivariable-adjusted logistic regression and combining cohort-specific estimates with meta-analysis were used to examine cohort associations. MR analyses were performed to assess the effect of genetically predicted prolactin levels on pregnancy outcomes and complications. Main Outcome Measures The primary outcome was live birth rate. Secondary outcomes included clinical pregnancy, biochemical pregnancy, miscarriage, preterm birth, and birthweight. Results A total of 8073 individuals were included, with mean age of 32 years, mean body mass index of 22 kg/m 2 , and mean serum prolactin levels of 14.6 ng/mL. Each 5 ng/mL increase in serum prolactin levels were significant associated with increased rate of live birth (odds ratio [OR]= 1.05, 95% confidence interval [CI] = 1.04 – 1.08; P < 0.001), clinical pregnancy (OR = 1.03, 95% CI =1.00–1.06; P = 0.03), biochemical pregnancy (OR = 1.04, 95% CI =1.00–1.07; P = 0.03), and decreased risk of miscarriage (OR =0.92, 95% CI = 0.88–0.97; P = 0.002). However, after adjusting for multiple confounders, the association between prolactin levels and live birth attenuated and became no longer statistically significant (adjusted OR [aOR] 1.03 per 5 ng/mL increase, 95% CI = 0.99–1.06; P = 0.10). Similarly, associations with clinical pregnancy (aOR = 1.02, 95% CI = 0.99–1.05; P = 0.26) and miscarriage (aOR = 0.96, 95% CI = 0.90–1.02; P = 0.14) also became non-significant after adjustment. Consistently, MR analysis indicated that genetically predicted prolactin levels were not significantly associated with live birth, miscarriage, preterm birth, birth weight, gestational diabetes mellitus, maternal hypertensive disorder, preeclampsia ( P > 0.05 for all). Conclusions Moderate increase in serum prolactin levels may not adversely affect pregnancy outcomes. The necessity of treatments for lowering prolactin before conception needs to be re-evaluated. Funding Source: National Natural Science Foundation of China (No. 82401908), Natural Science Foundation of Fujian Province of China (No. 2024J08309) Keywords: Prolactin, Pregnancy outcomes, Cohort study, Multi-centers, Mendelian randomization Tweetable Abstract: Moderately elevated prolactin (<100 ng/mL) does not adversely affect IVF pregnancy outcomes. Introduction Prolactin is synthesized and secreted by the lactotrophic cells of the anterior pituitary gland. Its primary role is to regulate milk secretion during the lactation period in mammals, but it also exerts pleiotropic effects on osmotic regulation, growth and development, as well as metabolism(1). Additionally, prolactin influences female reproductive health and the maintenance of pregnancy by regulating ovarian function and the menstrual cycle (2). Hyperprolactinemia can lead to amenorrhea, galactorrhea, anovulation, and infertility. While low prolactin levels were also associated with polycystic ovary syndrome and correlated with features of metabolic syndrome (3, 4). Due to the complex and multifactorial nature of pregnancy, the association between prolactin and pregnancy outcomes remains unclear. Clinical observations indicated that both elevated and reduced prolactin levels were associated with miscarriages (5-8). Therefore, a comprehensive evaluation of the association between prolactin and pregnancy outcomes is necessary. Due to insufficient sample size, lack of control for confounding factors, and absence of strict inclusion and exclusion criteria, the results of these studies may be subject to various biases. A multicenter design with large sample size is needed to further clarify the association between prolactin levels and pregnancy outcomes. Additionally, observational studies are inherently limited by residual confounding and are susceptible to reverse causality. Mendelian randomization (MR) analysis can address these issues by using genetic variations as instrumental variables (IVs). Since the alleles of genetic variations associated with exposure are randomly distributed at the population level during fertilization, MR helps mitigate confounding and reverse causality (9, 10), thereby enhancing the reliability of the inferences. This study aims to evaluate the nature of the association between serum prolactin levels and pregnancy outcomes. We explored the associations of prolactin levels and pregnancy outcomes through a multicenter retrospective cohort study and MR analysis. Methods Study design This is a multicenter retrospective cohort study and MR study, with the study design shown in Figure 1 . This study was approved by the ethics committees of the Women and Children’s Hospital of Ningbo University (2024KYSL-096), the First Affiliated Hospital of Wenzhou Medical University (KY2024-R263), Women and Children’s Hospital, School of Medicine, Xiamen University (KY-2024-121-K02). This paper followed per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline [19] ( Supplemental Materials ). Participants Data from women who underwent their first in vitro fertilization (IVF) fresh embryo transfer at three reproductive centers (Women and Children’s Hospital of Ningbo University; The First Affiliated Hospital of Wenzhou Medical University; Women and Children’s Hospital, School of Medicine, Xiamen University) between 2017 and 2023 were included. Women with prolactin < 100 ng/mL and who finished follow-up pregnancy outcomes were initially included. Individuals with thyroid, liver, and kidney dysfunctions (n=247), pituitary adenomas, malignant tumors, history of radiotherapy and chemotherapy, breast diseases (n=91), chromosomal and genetic abnormalities (n=125), recurrent pregnancy loss (n=67), uterine malformations (n=82), ovarian stimulation not using standard GnRH agonist or antagonist protocol (n= 83), missing serum prolactin data (n= 875), and those with severe oligozoospermia, asthenozoospermia, or teratozoospermia in the male partner (n=1361) were excluded ( Supplemental Figure 1 ). Measurement Age, body mass index (BMI), education, blood pressure, type of infertility, PCOS, endometriosis, baseline hormones (follicle-stimulating hormone [FSH], luteinizing hormone, estradiol), anti-Müllerian hormone (AMH), antral follicle counting (AFC), total cholesterol, triglyceride, high- and low-density lipoprotein were included as potential covariates. The anthropometric data of the patients were collected by nurses with at least 3 years of training experience. To diagnose PCOS, we applied the modified Rotterdam criteria (11). Endometriosis was identified according to International Classification of Diseases (tenth revision) code N80.0 (excluding N80.03). Sex hormones and Basal AFC were measured on days 2–4 of a natural menstrual cycle. Serum prolactin levels were measured between 9:00 and 11:00 AM, prior to undergoing IVF/intracytoplasmic sperm injection ovarian stimulation treatment. Blood lipids were measured after fasting. Sex hormones were analyzed using an ultrasensitive enzyme linked immunosorbent assay (Unicel Dxl 800, Beckman Coulter, Brea, CA). AMH was analyzed using an automated electrochemiluminescence immunoassay (ECLIA; Roche Diagnostics). Basal AFC was defined as the total number of small follicles (2-10mm in diameter) in both ovaries. Serum total cholesterol, triglyceride, high- and low-density lipoprotein were measured using an autoanalyzer (AU 5800, Beckman Coulter, Brea, CA). For the testing methods of biochemical parameters, both intra- and inter-assay variations were less than 10%. The primary endpoints of cohort study is the live birth rate. Secondary outcomes included clinical pregnancy (one or more gestational sacs under transvaginal ultrasound at 6-8 weeks of gestation), biochemical pregnancy (serum β-HCG concentration >5 mIU/mL at 2 weeks post-embryo transfer), miscarriage (before 28 weeks of pregnancy), preterm birth (delivery before 37 weeks of pregnancy), macrosomia (birthweight above 4000 g), low birth weight (birthweight less than 2500 g). Medical history information was collected by resident physicians or attending physicians specializing in reproductive medicine. All laboratory data were uniformly measured and reviewed by the laboratory department of these three tertiary hospitals. All original data was recorded in the hospital information systems, which only existed within the local area network. Standard IVF process All women underwent their first standard IVF treatment, including processes of ovarian stimulation, oocyte retrieval, IVF, fresh embryo transfer and subsequent follow-up of pregnancy outcomes. Ovarian stimulation protocols were tailored to each individual, taking into account factors such as age, BMI, and ovarian reserve. All treatments were provided by attending physicians with over 10 years of experience in assisted reproductive technology. Exogenous FSH preparations were administered for the induction and maintenance of growth of multiple dominant follicles. In most cases of this study, the exogenous FSH starting doses varied between 150 and 300 IU/d. After ovarian stimulation commencement, the subsequent FSH dosing was adjusted across the ovarian stimulation journey according to the results of the serum hormone levels and stimulated follicle sizes. Human chorionic gonadotropin at a dose of 4000 to 10,000 IU was administered to induce oocyte maturation when two or more follicles measured ≥18 mm. Oocyte retrieval was scheduled 32-36 hours later via transvaginal ultrasound. Based on sperm quality, oocytes were fertilized via IVF or ICSI approximately 4 to 6 hours after follicular aspiration, and fertilization was checked 16–18 hours later. One or two embryos were transferred transcervically on days 3-5 based on cleavage rate and morphology grading. Luteal phase support was provided until 10-12 weeks of gestation if pregnancy was confirmed. Statistical analysis Categorical variables were presented as numbers (percentages) and continuous variables were presented as mean (standard deviation [SD]). First, we performed data imputation for each cohort using the missRanger package (12, 13) . The data before and after imputation were compared to avoid bias. A two-stage analysis framework was employed. Firstly, logistic regression models were used to examine the association between prolactin levels and pregnancy outcomes in each cohort. Meta-analysis was performed to pool the estimate of each cohort using meta package (8.0-2). The heterogeneity between cohorts was assessed using the I ² statistic. The effect size obtained from the analysis represents the change in prolactin for each 5 ng/mL increase. Multivariate models were used to adjust for potential confounders. Model 1 adjusted for age, education, BMI, and systolic blood pressure (SBP). Model 2 further adjusted for infertility, endometriosis, PCOS, male factor, AMH, basal FSH, basal luteinizing hormone, total cholesterol, low-density lipoprotein, protocol, fertilization methods, and number of transferred embryos. Mendelian randomization study The IVs for prolactin was obtained from a genome-wide association studies (GWAS) conducted across 13 cohorts of European ancestry ( Supplemental Table 1 ), which is the largest publicly available GWAS summary statistics (14). SNPs associated with the exposure were selected a threshold of P < 5×10 -6 . The linkage disequilibrium of these SNPs was then estimated using the 1000 Genomes European reference panel. Independent variants with linkage disequilibrium r 2 < 0.001 in a clumping window of 10,000 kb were selected as IVs for prolactin ( Supplemental Table 2 ). To assess the bias due to weak instruments, the F-statistic was calculated to determine the strength of the IVs, with a conventional threshold of greater than 10. The formula is F = (N - K - 1 / K) (R 2 / 1 – R 2 ), where N represents the sample size, K is the number of IVs, and R 2 indicates the proportion of variance in the phenotype explained by the genetic instruments. Live births, miscarriage, preterm birth, birth weight, gestational diabetes and pregnancy-induced hypertension was used as the outcome, with detailed GWAS data information presented in Supplemental Table 1 . Inverse variance weighting (IVW) was used as the primary method to estimate effect sizes (15). In addition, the weighted median, weighted mode, and MR-Egger methods were used as sensitivity analyses (16, 17). MR-Egger method was used to detect and adjust for any potential pleiotropic effects that may violate the exclusion restriction assumption (16). Cochran’s Q test and the I ² statistic were used to examine the heterogeneity of SNP estimates in each association (15, 18). For binary outcomes, MR estimates are presented as odds ratios (OR) with 95% confidence intervals (CI), while for continuous outcomes, the estimates are represented as β. TwoSampleMR package (v0.6.0.) were used in the analysis. We followed the STROBE-MR guidelines for reporting Mendelian randomization studies (19) ( Supplemental Materials ). A two-tailed P < 0.05 was considered statistically significant throughout the study. All analyses and data visualization were conducted using R version 4.4.2 (Vienna, Austria). Results The baseline characteristics of the study population The study design was presented in Figure 1 . A total of 8073 individuals was included in final analysis, with mean age of 32.0 years (SD 4.38), mean BMI of 22.0 kg/m 2 (SD 3.00), and mean prolactin of 14.6 ng/mL (SD 8.29). The participant of three centers presented a similar profile of ovarian reserve, with mean AMH of 3.8 ng/mL (SD 2.97), mean AFC of 13.0 (SD 7.94), and mean basal FSH of 7.71 IU/L (SD 2.94). Among the participants, 5317 (65.9%) had a biochemical pregnancy, and 4642 (57.5%) had a clinical pregnancy. 727 (15.7%) individuals experienced a miscarriage, while 493 (16.6%) had preterm births. Live birth occurred in 3877 (48.0%) women. Low birth weight was observed in 668 (17.2%) individuals, and macrosomia was present in 131 (3.38%). There was no significant difference between the distribution of imputed data and that of the original complete case data ( P > 0.05, Supplemental Tables 3-5 ). Associations between prolactin levels and pregnancy outcomes in univariate analysis Figure 2 showed summary estimates for the cohort-specific associations between prolactin levels and pregnancy outcomes ( Supplemental Table 6 ). The pooled results showed that for every 5 ng/mL increase in serum prolactin levels, the live birth rate increased by 5% (OR = 1.05, 95% CI = 1.04–1.08; P＜0.001), the biochemical pregnancy rate increased by 4% (OR = 1.04, 95% CI = 1.00–1.07; P = 0.03), the clinical pregnancy rate increased by 3% (OR = 1.03, 95% CI = 1.00–1.06; P = 0.03), and the miscarriage rate decreased by 8% (OR = 0.92, 95% CI = 0.88–0.97; P = 0.002). No significant associations between prolactin and preterm birth, macrosomia, or low birth weight was observed ( Supplemental Table 7) . In Ningbo cohort, serum prolactin levels were found to be associated with a higher live birth rate (OR=1.07, 95%CI: 1.02–1.12; P = 0.003) and a lower miscarriage rate (OR=0.87, 95%CI: 0.77–0.96; P = 0.01). Consistently, a positive association (OR=1.05, 95%CI: 1.00–1.09; P = 0.03) between prolactin levels and live birth was observed in Xiamen cohort. However, in Wenzhou cohort, no association was found between prolactin levels and pregnancy outcomes. Associations between prolactin levels and pregnancy outcomes in multivariate analysis In the primary multivariate analysis (Model 1), the pooled estimate for the association between each 5 ng/mL increase in serum prolactin and live birth was attenuated compared to the univariate analysis and did not reach statistical significance (adjust OR [aOR] = 1.03, 95% CI 0.99–1.06; P = 0.10) ( Figure 3 and Supplemental Table 8 ). While statistically non-significant, the confidence interval suggested that a minor positive association cannot be entirely excluded. Further adjustment for infertility type, endometriosis, PCOS, male factor, ovarian reserve markers (AMH, basal FSH, LH), lipids, ovarian stimulation protocol, fertilization method, and number of embryos transferred (Model 2) yielded consistent results (aOR = 1.03, 95% CI 0.99–1.06; P = 0.12). The associations with biochemical pregnancy (Model 1 aOR = 1.02, 95% CI 0.99–1.05; P = 0.32), clinical pregnancy (Model 1 aOR 1.01, 95% CI 0.98–1.04; P = 0.36), and miscarriage (Model 1 aOR 0.96, 95% CI 0.90–1.02; P = 0.07) were also non-significant in the adjusted models. Cohort-specific analysis revealed that the positive association between prolactin and live birth (aOR 1.06, 95% CI 1.01–1.11; P = 0.02) and the negative association with miscarriage (aOR 0.88, 95% CI 0.79–0.98; P = 0.03) remained statistically significant in the Ningbo cohort even after full adjustment in Model 2. In contrast, no significant associations were observed in the Wenzhou or Xiamen cohorts ( Supplemental Tables 9, 10 and Supplemental Figures 3, 4 ). Mendelian randomization study In the MR analysis, 15 IVs were extracted from the largest available GWAS dataset of prolactin, with F-statistics greater than 10 ( Supplemental Table 2 ). Using the traditional IVW method, no significant association was found between the gene-predicted serum prolactin levels and number of live births, miscarriage, preterm birth, and birth weight ( Table 2 ). In addition, no association was found between prolactin levels and gestational diabetes or gestational hypertensive disorders. Consistently, using other models such as Weighted Median, Weighted Mode, and Simple Mode, no evidence was found to support an association between prolactin levels and pregnancy outcomes or pregnancy complications ( Supplemental Table 11 ). Heterogeneity was observed only when birth weight was used as the outcome. We did not detect any evidence of directional pleiotropy through the MR-Egger intercept test ( MR-Egger P > 0.05 for all) ( Supplemental Table 12 ). Discussion Main Findings This study showed that there were no significant independent associations between serum prolactin levels and pregnancy outcomes, including live birth, miscarriage, preterm birth, and birth weight. Consistently, MR analysis did not identify any association between genetically predicted prolactin levels and pregnancy outcomes. These results indicated that moderately elevated prolactin levels might not be detrimental to pregnancy outcomes. Strengths and Limitations This study has several strengths. First, this is a multi-center study with a larger and more diverse population, which enhances the generalizability and external validity of the findings. Secondly, stringent exclusion criteria were established to minimize the inclusion of cases with pathological elevations of prolactin levels, thereby enhancing the validation. Additionally, MR analysis provides estimates that are less susceptible to confounding and reverse causality bias. The study also has limitations. Due to the retrospective nature of the study, we were unable to assess other potential confounding factors that could influence pregnancy outcomes, such as smoking and nutritional supplementation. Additionally, the GWAS data used in the MR analysis were derived from a European population, emphasizing the need for validation in other ethnic populations. Interpretation Previous observational studies have shown that prolactin levels are significantly elevated in women with recurrent miscarriages, leading to luteal phase defects and miscarriages, which may be related to the effect of prolactin on ovarian function and the uterine endometrial environment (5-7). Consistently, some studies have found that elevated prolactin levels during IVF process may reduce fertilization rate (20, 21). However, other studies hold an opposing view, suggesting that hyperprolactinemia is positively correlated with pregnancy success rate (20, 21). A positive correlation was observed between basal prolactin levels above 30 ng/mL and clinical pregnancy, with levels above 40 ng/mL being a good indicator of live birth rate (21). Besides, some studies have reported similar pregnancy rate and pregnancy outcomes between populations with elevated baseline prolactin levels or increased prolactin levels during IVF and those with normal prolactin levels (22-24). Our analyses showed that the significant association between prolactin levels and both live birth rate and miscarriage rate disappeared after adjusting for confounders, suggesting that prolactin is not an independent determinant of pregnancy outcomes. Consistently, MR analysis further supported this finding. Notably, in the Ningbo cohort, after adjusting for confounding factors using two models, prolactin levels have demonstrated a robust significant association with higher live birth rate and lower miscarriage rate. Our findings suggest that moderate variations in prolactin levels may not be sufficient to independently influence pregnancy outcomes. Elevated prolactin is known to impair female reproduction by suppressing GnRH, reducing gonadotropins, disrupting estrogen feedback, and causing anovulation. Elevated prolactin in follicular fluid directly inhibited granulosa cell aromatase activity and estrogen synthesis (25, 26). Additionally, clinical evidence supports the inhibitory effect of high prolactin levels on the corpus luteum, leading to insufficient luteal phase and lower progesterone levels (27). However, increasing evidence has highlighted the beneficial effects of prolactin in female reproduction that support homeostasis during pregnancy. First, follicular fluid prolactin levels help improve oocyte maturity and fertilization potential (28-30). Moreover, prolactin promotes early luteal formation and survival, enhances blastocyst implantation potential, and plays a crucial role in maintaining pregnancy (31-33). Animal model studies suggest that β-cell expansion during pregnancy is dependent on prolactin (34, 35). In humans, low circulating levels of prolactin during pregnancy are a risk factor for postpartum diabetes (34). Treatment of hyperprolactinemia before conception has yielded conflicting results in previous studies. Evidence from several research suggested that managing transient hyperprolactinemia was associated with improved fertilization and pregnancy rate (36, 37). While other studies have shown that treatment for hyperprolactinemia does not significantly improve fertilization or live birth rates(38, 39). However, patients with mildly elevated prolactin levels who were not treated prior to ovarian stimulation had higher-quality oocytes and fertilization rate (40). Our findings suggest that elevated prolactin levels prior to conception may not require aggressive intervention. However, the possibility for the association between prolactin and pregnancy outcomes cannot be entirely excluded, underscoring the need for further investigation. Conclusion In conclusion, this multi-center cohort study, complemented by MR analysis, found no evidence supporting an independent association between moderately elevated serum prolactin levels (<100 ng/mL) and key pregnancy outcomes, including live birth and miscarriage. Re-evaluation of treatment necessity for moderate, asymptomatic prolactin elevation prior to conception appears justified based on this evidence. Abbreviations MR: mendelian randomizationIVs: instrumental variablesIVF: in vitro fertilizationBMI: body mass indexFSH: follicle-stimulating hormoneAMH: anti-Müllerian hormoneAFC: antral follicle counting SD: standard deviationSBP: systolic blood pressureGWAS: genome-wide association studiesIVW: inverse variance weightingOR: odds ratiosCI: confidence intervals Authors’ contributions G.W., Z.C., and H.Y. designed this study. Y.S., Z.S., Y.C., Z.D., X.P., and X.L. prepared the initial draft, analysed the data, and finalised the manuscript with comments from all other authors. G.W., Y.L., P.W., X.C., and L.Z. collected and analysed the data. L.W., W.X., and X.H. validated the data. G.W., X.D., L.H., and P.L. made important revisions to the manuscript. H.G. and L.L. participated in the interpretation of the data and provided important comments on the manuscript. All authors reviewed the draft critically and approved the final version. Acknowledgements We thank all the participants and research staff who took part in the Ningbo, Wenzhou, and Xiamen cohorts for their contributions. We also want to acknowledge the participants and investigators of the FinnGen study, the Early Growth Genetics Consortium, as well as other researchers who provided publicly available GWAS data for the MR analyses. Availability of data and materials All GWAS data used in the study are publicly available. The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. Clinical trial registration number This study was registered in the China Clinical Trial Registration Center (ChiCTR2500095111). Declarations Ethics approval and consent to participate This study was approved by the ethics committees of the Women and Children’s Hospital of Ningbo University (2024KYSL-096), the First Affiliated Hospital of Wenzhou Medical University (KY2024-R263), Women and Children’s Hospital, School of Medicine, Xiamen University (KY-2024-121-K02) and registered in the China Clinical Trial Registration Center (ChiCTR2500095111). Informed consent was waived due to deidentified data. Competing interests The authors declare that they have no competing interests. References: 1. Bernard V, Young J, Binart N. Prolactin - a pleiotropic factor in health and disease. Nat Rev Endocrinol 2019 Jun;15(6):356-65.2. Iancu ME, Albu AI, Albu DN. Prolactin Relationship with Fertility and In Vitro Fertilization Outcomes-A Review of the Literature. Pharmaceuticals (Basel) 2023 Jan 13;16(1).3. Albu A, Florea S, Fica S. 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The pooled estimate of the multivariate analysis. Abbreviation: OR, odds ratio; CI, confidence interval. Supplementary Material File (supplemental information.docx) Download 18.82 KB File (supplemental table.xlsx) Download 38.62 KB File (table 1.docx) Download 28.70 KB File (table 2.docx) Download 17.58 KB Information & Authors Information Version history V1 Version 1 13 February 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords fertility and assisted reproduction reproductive science: sex steroids Authors Affiliations Yingying Shi The Affiliated Women and Children's Hospital of Xiamen University View all articles by this author Zhuxian Shi The Affiliated Women and Children's Hospital of Xiamen University View all articles by this author Yi Chen The First Affiliated Hospital of Wenzhou Medical University View all articles by this author Ziyin Ding Ningbo Women and Children's Hospital View all articles by this author Xin Pan Wenzhou Medical University View all articles by this author Xiaojing Lin The First Affiliated Hospital of Wenzhou Medical University View all articles by this author Shanghui Xie The First Affiliated Hospital of Wenzhou Medical University View all articles by this author Xile Cai Zhejiang University School of Medicine View all articles by this author Yan Li The First Affiliated Hospital of Wenzhou Medical University View all articles by this author Peiyu Wang The First Affiliated Hospital of Wenzhou Medical University View all articles by this author Wanyi Xie Peking University Third Hospital View all articles by this author Haijie Gao The Affiliated Women and Children's Hospital of Xiamen University View all articles by this author Xuemei He The Affiliated Women and Children's Hospital of Xiamen University View all articles by this author Luping Li The Affiliated Women and Children's Hospital of Xiamen University View all articles by this author Ping Li The Affiliated Women and Children's Hospital of Xiamen University View all articles by this author Liming Zhou Ningbo Women and Children's Hospital View all articles by this author Haiyan Yang The First Affiliated Hospital of Wenzhou Medical University View all articles by this author Zimiao Chen The First Affiliated Hospital of Wenzhou Medical University View all articles by this author Guiquan Wang 0000-0002-6434-1627 [email protected] The Affiliated Women and Children's Hospital of Xiamen University View all articles by this author Metrics & Citations Metrics Article Usage 228 views 79 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Yingying Shi, Zhuxian Shi, Yi Chen, et al. 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