Clinical significance and biological roles of lncRNA CTBP1-AS in Polycystic Ovary Syndrome

Clinical significance and biological roles of lncRNA CTBP1-AS in Polycystic Ovary Syndrome | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical significance and biological roles of lncRNA CTBP1-AS in Polycystic Ovary Syndrome Li Qin, Chun Tian, Liying Huang, Xiao Qin, Shaohua Ling, Jingxi Wei, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5252234/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Dec, 2024 Read the published version in Journal of Ovarian Research → Version 1 posted 10 You are reading this latest preprint version Abstract Polycystic ovary syndrome (PCOS) is among the most prevalent endocrine and metabolic disorders affecting women of reproductive age. Multiple factors, including genetic predisposition, environmental influences, and lifestyle choices, are considered significant contributors to the development of PCOS. A kind of long noncoding RNA—C-Terminal binding protein 1 antisense (lncRNA CTBP1-AS ) has been proven to be a new androgen receptor regulator. Previous studies showed that the lncRNA CTBP1-AS gene was highly expressed in a small sample of PCOS patients and was associated with the risk of PCOS, but its specific function and mechanism have not been clearly reported. In this study, the expression of lncRNA CTBP1-AS was detected by real-time quantitative PCR (RT-qPCR) in PCOS patients. In addition, lncRNA CTBP1-AS was overexpressed in KGN cells to explore its effect on granulocyte function. The results showed that the expression levels of lncRNA CTBP1-AS were increased in serum single nucleated cells and follicular fluid granulosa cells of PCOS patients compared with controls, which correlated with androgen levels and sinus follicle number; overexpression of lncRNA CTBP1-AS increased apoptosis and decreased cell migration ability, thus promoting the progression of PCOS. This study explores new biomarkers and therapeutic targets for the clinical individualised diagnosis and treatment of PCOS. Polycystic ovary syndrome lncRNA CTBP1-AS Expression regulation Granulosa cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Polycystic ovary syndrome (PCOS), a common heterogeneous endocrine and metabolic disorder, is one of the most common reproductive endocrine disorders in women of childbearing age, affecting up to 20% of women worldwide [ 1 , 2 ] . The etiology and pathogenesis of PCOS are complex and influenced by environmental, psychological, and genetic factors, but the exact etiology has not yet been identified [ 3 ] . The clinical manifestations of PCOS are highly heterogeneous, and there is no specific treatment in the clinic. For women of childbearing age, the main treatment is ovulation promotion and assisted reproduction techniques, and for women who have no requirement for childbearing, the prevention and treatment of long-term complications and metabolic syndrome should also be carried out, and such metabolic and endocrine disorders may affect the whole life of a woman [ 4 , 5 ] . Therefore, the diagnosis and treatment of PCOS still need to be further researched into its pathogenesis-related factors and progression mechanisms, to identify new diagnostic and therapeutic targets, provide early diagnosis of PCOS patients, and provide new and better individualized diagnostic and therapeutic methods. Long noncoding RNA of C-Terminal binding protein 1 antisense (lncRNA CTBP1-AS ) is a newly discovered long noncoding RNA [ 6 ] . lncRNA CTBP1-AS , a potential androgen receptor regulator, functions in the androgen receptor (AR) signaling pathway [ 7 , 8 ] . Aberrant expression of AR can lead to enhanced activation of otherwise normal levels of androgens (testosterone and dihydrotestosterone) in the body, resulting in hyperandrogenemia [ 9 ] . The available evidence suggests that metabolic disturbances due to hyperandrogenemia are one of the important features of the pathological changes in PCOS [ 10 ] . The lncRNA CTBP1-AS as a new androgen-regulated long noncoding RNA has gradually attracted the attention of many scholars [ 11 ] . Previous studies have found that lncRNA CTBP1-AS is associated with the development of PCOS, but their study samples are small and still need to expand the sample size for further studies. Previous studies have found that lncRNA CTBP1-AS is associated with the pathogenesis of PCOS, but their samples are small and limited to the detection of a single type of cell in patients with PCOS. The influence of lncRNA CTBP1-AS on the occurrence and development of PCOS as well as a clear mechanism of action still requires further study [ 12 , 13 ] . Our study aimed to further explore the correlation between lncRNA CTBP1-AS and the pathogenesis of PCOS by expanding the sample size and investigate the functional effects of lncRNA CTBP1-AS on ovarian GCs by cellular assays. This study confirmed the functional role of lncRNA CTBP1-AS in the occurrence and development of PCOS, and explored new targets for molecular diagnosis and gene therapy of PCOS. Materials and methods Study population In this study, a case-control study was used, and patients who visited the Reproductive Medicine Center of the Affiliated Hospital of Youjiang Medical University for Nationalities in Guangxi from January 2018 to March 2019 were selected for the study. Patients with polycystic ovary syndrome served as the case group, and age-matched patients who underwent assisted reproductive technology for fertilization due to tubal factors or male factors were selected as the control group. (1) A total of 125 peripheral blood specimens were collected, including 85 cases in the case group and 40 cases in the control group; the mean age was 27.38 ± 4.35 years. Inclusion criteria were as follows: 1) Case group: The diagnostic criteria for PCOS were based on the Rotterdam criteria recommended by ESHRE/ASRM in 2003: 1) oligo-ovulation and/or anovulation (OA); 2) increased serum androgen levels and/or hyperandrogenism (HA); 3) polycystic ovarian changes. The presence of two of the above three items at the same time needs to rule out other diseases, such as Cushing syndrome, congenital adrenal hyperplasia, and other diseases causing high androgen, as well as hyperprolactinemia and other diseases causing abnormal ovulation. ②Control group: patients with infertility due to tubal or male factors, regular menstruation (menstrual cycle of 28 ± 7 days), no clinical signs of hyperandrogenism, normal ovulation by ultrasound monitoring, and normal morphology of both ovaries during the same period. (2) A total of 30 follicular fluid specimens were collected, 13 in the case group and 17 in the control group; the mean age was 32.87 ± 4.15 years. The inclusion criteria were as follows: ① Case group: patients with PCOS who underwent in vitro fertilization and embryo transfer (IVF-ET) for the first time due to female factor (diagnostic criteria as before). ②Control group: patients who underwent IVF-ET for the first time due to tubal factor infertility, with regular menstruation, no clinical manifestations of hyperandrogenism, and no abnormality in the morphology of bilateral ovaries under ultrasound. All subjects included in the study were excluded from a history of ovarian surgery or radiotherapy, endometriosis, uterine fibroids, endometrial polyps, uterine malformations, uterine adhesions, history of pelvic tuberculosis, systemic diseases, and hereditary diseases, and there was no history of hormonal medications in the last 3 months, and other preoperative physical examinations showed no significant abnormalities. The study subjects had complete clinical information, and no significant difference was observed in the age composition ratio of each group (P > 0.05). The study protocol was approved by the Ethics Committee of the hospital, and specimens were collected after the subjects themselves signed informed consent. Table 1 Clinical indicators of peripheral blood samples Clinical indicators PCOS (N = 85) Control(N = 40) t / Z p value Age(years) 26(24,29) 28(24, 31) -1.397 0.163 Duration of infertility (years) 2(1, 4) 2(1, 4) -0.51 0.61 Menstrual cycles(days) 68(60, 90) 31(30, 40) -7.907 < 0.001* Antral follicle count 31(28, 40) 18(15, 20) -8.358 < 0.001* Basic sex hormone FSH (IU/L) 5.78 ± 1.84 5.81 ± 1.78 -0.095 0.925 LH (IU/L) 8.67(5.53, 12.60) 4.16(3.64, 5.39) -5.547 < 0.001* E2 (pg/mL) 56.0(45.0, 68.5) 47.0(38.0, 59.7) -2.844 0.004* P (ng/mL) 0.46(0.30, 0.70) 0.49(0.22, 0.60) -0.506 0.613 T (ug/L) 0.76 ± 0.27 0.47 ± 0.19 6.253 < 0.001* PRL (ug/L) 12.58 ± 5.74 10.80 ± 4.84 1.7 0.092 AMH (ng/mL) 7.55(5.00,10.62) 4.48(2.37, 6.48) -4.701 < 0.001* FPG (mmol/L) 4.87(4.60, 5.23) 4.75(4.52, 5.15) -1.5 0.134 FINS (pmol/L) 75.0(58.1, 89.1) 52.0(40.5, 68.5) -4.01 < 0.001* HOMAIR 2.44(1.77, 2.91) 1.57(1.26, 2.08) -4.319 < 0.001* BMI (kg/m 2 ) 22.7(20.1, 24.9) 21.3(19.1, 24.9) -1.527 0.127 Data are presented as the mean ± standard deviation, or median (interquartile range). FSH, follicle-stimulating hormone; LH, luteinizing hormone; E2, estradiol; P, progestogens; T, testosterone; PRL, prolactin; AMH, anti-mullerian hormone; FPG, Fasting Plasma Glucose; FINS, Fasting Insulin; HOMA-IR, homeostatic model assessment of insulin resistance; BMI, body mass index; *P < 0.05 indicates a statistically significant association between the variables. Cell culture and cell transfection Human ovarian granulosa cells KGN were purchased from the Cell Bank of the Chinese Academy of Sciences. Cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) containing 10% fetal bovine serum (Ausgenex), penicillin (100 U/mL, Solarbio), and puromycin (100 µg/mL, Thermofisher). 293A and 293T cells were purchased from the Cell Bank of the Chinese Academy of Sciences, and the lncRNA CTBP1-AS overexpression plasmid was purchased from Suzhou Ltd. Adenovirus after successful packaging were transfected into the cultured KGN cells at Polybrene 4 µg/ml, MOI = 5 conditions, and the fluorescence expression was observed 48–72 hours after infection. Table 2 Clinical indicators of granulocyte samples Clinical indicators PCOS (N = 13) Control(N = 17) t / Z p value Age(years) 31.92 ± 4.59 33.59 ± 3.76 1.093 0.284 Duration of infertility (years) 3(2, 5) 3(2,4) -0.301 0.764 Menstrual cycles(days) 60(37, 90) 30(30, 33) -3.656 < 0.001* Antral follicle count 24(19,30) 14(11, 16) -3.558 < 0.001* Basic sex hormone FSH (IU/L) 5.70(5.1, 6.35) 6.68(5.09, 8.64) -1.612 0.107 LH (IU/L) 5.43(2.75, 11.48) 3.60(2.71, 4.73) -1.78 0.075 E2 (pg/mL) 43.31 ± 12.61 54.18 ± 22.97 1.535 0.136 P (ng/mL) 0.36 ± 0.19 0.45 ± 0.18 1.352 0.187 T (ug/L) 0.50 ± 0.17 0.43 ± 0.16 -1.192 0.243 PRL (ug/L) 11.37(8.63,13.59) 12.3(9.99,17.45) -1.089 0.276 AMH (ng/mL) 7.12 ± 3.13 3.42 ± 1.77 -3.829 0.001* FPG (mmol/L) 5.05(4.58, 5.36) 4.80(4.60, 5.15) -1.219 0.223 FINS (pmol/L) 58.92 ± 10.78 51.01 ± 15.15 -1.596 0.122 HOMAIR 1.88 ± 0.32 1.59 ± 0.53 -1.749 0.091 BMI (kg/m 2 ) 21.44 ± 1.73 21.95 ± 2.36 0.66 0.515 *P < 0.05 indicates a statistically significant association between the variables. CCK-8 assa CCK-8 assay was used to measure cell proliferation. In the presence of 1-Methoxy PMS, WST-8 in the reagent was reduced by dehydrogenases in the cells to a highly water-soluble yellow formazan product (Formazan dye). The number of produced formazan products was proportional to the number of living cells. The OD value of the optical density at 450 nm, measured using an enzyme marker, reflected the change in the number of living cells, thus detecting differences in proliferation produced by different cells over time. Flow cytometry The cells were digested and centrifuged at 200 g. The supernatant was discarded. The cells were resuspended with 50 µL 1× Binding Buffer, and the dyes were added according to the following groups: without any dye (negative control), 5 µL Annexin V-APC (single positive control), 10µL 7-AAD (single positive control), 5 µL Annexin V-FITC and 10 µL PI (sample tube). The mixture was incubated for 15 minutes in the dark. The apoptosis rate was analyzed by flow cytometer (BD Biosciences). Cell scratching assay Cells were seeded in transwell chambers, and the chambers were immersed in 2% serum medium outside the chambers. 24 hours later, the chambers were removed, and the cells flanking the outside of the chambers were stained and photographed with a light microscope. Table 3 Correlation between lncRNA CTBP1-AS expression levels in peripheral blood mononuclear cell and clinical parameters Clinical indicators Expression of lncRNA CTBP1-AS(N = 125) r p Age(years) 0.173 0.053 Duration of infertility (years) 0.088 0.328 Menstrual cycles(days) 0.134 0.136 Antral follicle count 0.194 0.030* Basic sex hormone FSH (IU/L) 0.054 0.549 LH (IU/L) 0.083 0.357 E2 (pg/mL) -0.056 0.537 P (ng/mL) -0.032 0.726 T (ug/L) 0.202 0.024* PRL (ug/L) 0.048 0.593 AMH (ng/mL) 0.149 0.098 FPG (mmol/L) -0.019 0.835 FINS (pmol/L) 0.087 0.332 HOMAIR 0.065 0.473 BMI (kg/m2) 0.056 0.536 *P < 0.05 indicates a statistically significant association between the variables. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) Total RNA was extracted by using AxyPrep Total RNA Small Volume Preparation Kit, and the extracted RNA was detected by applying a nucleic acid quantifier, including the content and purity. The RNA with qualified purity and concentration was subjected to reverse transcription using the Reverse Transcription Reaction Kit (Fermentas Inc., USA). Then, lncRNA CTBP1-AS and the internal reference GAPDH were amplified by PCR, and a sample from the same normal group was added as a reference sample for each RT-qPCR. The reaction system for RT-qPCR was 20 µl, consisting of 3 µl F, 3 µl R, 3 µl DEPC, 1 µl cDNA and 10 µl SYBR. The reaction conditions were: 95 ℃ for 10 min pre-denaturation followed by 95 ℃ for 15 s and 60 ℃ for 1 min for 40 cycles. Three replicate measurements were taken for each sample to ensure accurate results. The Ct mean values of each sample lncRNA CTBP1-AS and GAPDH were first calculated separately, and then the data were used to calculate the relative quantity (RQ) of expression using the 2-ΔΔCT method. Statistical analysis SPSS 13.0 software was used for statistical processing. Measurement data conforming to normal distribution were expressed as ‾x ± s, and comparison of data between groups should be made by t-test or ANOVA according to the nature of the data; if they did not conform to normal distribution they were expressed as median (M) and quartiles (P 25 , P 75 ), and comparison between groups was changed to rank sum test. Count data were expressed as rates (%), and comparisons between groups were made using the four-cell χ 2 test or Fischer’s exact test. Correlations between variables were analyzed by Pearson or Spearman's rank correlation analysis, multiple linear regression analysis. A value of P < 0.05 was considered statistically significant. Results General clinical information In the clinical data of peripheral blood samples, age, duration of infertility, basal FSH, P, PRL, FPG, and BMI levels of two study groups were compared and the differences were not statistically significant. The menstrual cycle, antral follicle count, basal LH, E2, T, AMH, FINS, and HOMAIR levels were higher in the PCOS group than in the control group, and the difference was statistically significant (Table 1 ). In the clinical data of granulocyte samples, age, duration of infertility, and BMI level of the two study Table 4 Correlation between lncRNA CTBP1-AS expression levels in in GCs and clinical parameters Clinical indicators Expression of lncRNA CTBP1-AS(N = 30) r p Age(years) -0.369 0.045* Duration of infertility (years) 0.262 0.161 Menstrual cycles(days) 0.455 0.012* Antral follicle count 0.312 0.093 Basic sex hormone FSH (IU/L) -0.157 0.408 LH (IU/L) 0.005 0.98 E2 (pg/mL) -0.09 0.636 P (ng/mL) 0.098 0.608 T (ug/L) -0.056 0.771 PRL (ug/L) 0.101 0.595 AMH (ng/mL) 0.212 0.261 FPG (mmol/L) 0.305 0.102 FINS (pmol/L) 0.044 0.818 HOMAIR 0.122 0.521 BMI (kg/m2) -0.294 0.114 *P < 0.05 indicates a statistically significant association between the variables. groups were compared and the difference was also not statistically significant. After pretreatment of the study subjects who entered the IVF-ET cycle, the differences in basal FSH, LH, E2, PRL, P, and T were not statistically significant when comparing the pre-superovulation sex hormone levels between the two groups. FPG, FINS, and HOMAIR in the PCOS group were higher than those in the control group, but the difference was not statistically significant. It suggested the two groups were more balanced in terms of sex hormones and other indicators at the time of entry into the treatment cycle, and the follow-up studies were comparable. The menstrual cycle, antral follicle count, and AMH were higher in the PCOS group than in the control group (Table 2 ). The expression of lncRNA CTBP1-AS in peripheral blood mononuclear cells and follicular fluid GCs In our study, we found that patients with PCOS had a higher lncRNA CTBP1-AS level in peripheral blood mononuclear cells, compared with controls(0.86 ± 0.43 vs. 0.71 ± 0.29, P = 0.034) (Fig. 1 A). To better study the clinical heterogeneity of PCOS, we further divided the PCOS group into several subgroups according to the Rotterdam criteria and the main clinical characteristics (hyperandrogenemia and insulin resistance), respectively, and analyzed them statistically using the control group as a reference. They were categorized into 4 subtypes according to the Rotterdam criteria: complete OA + HA + PCO (n = 33), ovulatory HA + PCO (n = 4), non-hyperandrogenic OA + PCO (n = 39), and classic OA + HA (n = 9); Four subgroups were categorized according to the two main clinical features of hyperandrogenemia and insulin resistance: the hyperandrogenic group HA (n = 36), the insulin-resistant group IR (n = 14), the hyperandrogenic + insulin-resistant group HA + IR (n = 10), and the no hyperandrogenic and insulin-resistant group NONE (n = 25). Table 5 Correlation of follicular fluid granulosa cell lncRNA CTBP1-AS expression levels with IVF-ET indicators Clinical indicators Expression of lncRNA CTBP1-AS(N = 30) r p Gn Days of use (d) -0.233 0.215 Total Gn (IU) -0.399 0.029* HCG day Endometrium(mm) -0.211 0.262 E2 (pg/mL) 0.334 0.071 No. of oocytes retrieved 0.026 0.891 No. of MII oocytes 0.018 0.927 No.of fertilized oocytes -0.065 0.734 No. of cleavage embryos -0.118 0.534 No. of good-quality embryos 0.15 0.429 *P < 0.05 indicates a statistically significant association between the variables. Statistical analysis of the four subtypes of the Rotterdam criteria for PCOS (Fig. 1 B) revealed a statistically significant difference between the elevated expression of the lncRNA CTBP1-AS in complete PCOS only compared with controls(1.01 ± 0.47 vs. 0.71 ± 0.29, P = 0.001). In contrast, the expression of lncRNA CTBP1-AS in ovulatory PCOS (0.81 ± 0.38) and non-hyperandrogenic PCOS (0.76 ± 0.40) was elevated compared with the control group, but the difference was not statistically significant; the expression of lncRNA CTBP1-AS in classic PCOS (0.70 ± 0.16 ) was not significantly different from the control group. Further two-by-two comparisons revealed that lncRNA CTBP1-AS expression in complete PCOS also differed from classic, non-hyperandrogenic PCOS and not from ovulatory PCOS. Statistical analysis of the four subgroups with the main clinical features of PCOS (hyperandrogenemia and insulin resistance) versus the control group (Fig. 1 C) revealed that the expression of lncRNA CTBP1-AS was elevated in the hyperandrogenemia group, and in the hyperandrogenemia + insulin resistance group, and the difference was statistically significant (0.88 ± 0.41 vs. 0.71 ± 0.29, P = 0.031; 1.09 ± 0.51 vs. 0.71 ± 0.29, P = 0.004); the mean expression level of lncRNA CTBP1-AS was also elevated in the non-hyperandrogenemia + insulin resistance group (0.80 ± 0.44) compared to the control group, but none of the differences were statistically significant (P > 0.05); in the insulin resistance group (0.70 ± 0.31) the mean expression level of lncRNA CTBP1-AS was not significantly different from the control group. Further two-by-two comparisons revealed that the lncRNA CTBP1-AS expression in the hyperandrogenemia + insulin resistance group also differed from the insulin resistance group, the non-hyperandrogenemia + insulin resistance group (P < 0.05), and did not differ from the hyperandrogenemia group. The mean expression level in GCs was higher in PCOS patients than in controls [0.39 (0.18, 0.66) vs. 0.17 (0.10, 0.34), P = 0.043] (Fig. 1 D). The correlation between lncRNA CTBP1-AS transcript levels and clinical parameters Pearson or Spearman's rank correlation analysis was applied to analyze the correlation between lncRNA CTBP1-AS transcript levels and clinical parameters. The results showed that lncRNA CTBP1-AS in peripheral blood mononuclear cells was correlated with sinus follicle number and androgen levels (Table 3 ); lncRNA CTBP1-AS transcript levels in GCs were negatively correlated with the age of the subjects and positively correlated with menstrual cycle; lncRNA CTBP1-AS levels in GCs were negatively correlated with the total amount of Gn in the subjects (Table 4 ). The results of the correlation analysis between granulosa cell lncRNA CTBP1-AS transcript levels and IVF parameters showed a negative correlation between lncRNA CTBP1-AS levels and the total amount of Gn in the subjects (Table 5 ). Adenovirus of lncRNA CTBP1-AS overexpression infects ovarian granulosa cells We hypothesized that the lncRNA CTBP1-AS may be involved in the pathologic process of PCOS development by affecting the function of GCs and normal follicular development. To confirm the role of lncRNA CTBP1-AS in the pathogenesis of PCOS, lncRNA CTBP1-AS overexpression adenovirus was applied to infect KGN cells. According to the results of the pre-experiment, the optimal viral transfection conditions were obtained as Polybrene 4 µg/ml, MOI = 5, and the infection efficiency reached more than 90% as seen under the inverted fluorescence microscope after 48h of transfection (Fig. 2 A), which can be used for the subsequent cell function experiments. Total RNA was extracted from KGN cells after 48 hours of adenovirus infection, and the overexpression and silencing efficiencies were detected by RT- regulated more than 3000-fold in KGN cells that overexpressed the lncRNA CTBP1-AS (Over qPCR using empty virus (Negative Control, NC) and wild type KGN's cells not infected with the virus (Wild Type, WT) as a control, and the results showed that the expression of lncRNA CTBP1-AS was up- Expression, OE), whereas the difference in lncRNA CTBP1-AS expression between NC and WT was not statistically significant (Fig. 2 B) Table 6 The results of Cell Cycle Cell Cycle(%) WT NC OE G0-G1 58.47 ± 3.25 61.65 ± 2.58 63.14 ± 3.84 S 31.64 ± 1.65 26.81 ± 1.84 27.25 ± 3.54 G2-M 9.89 ± 1.10 11.54 ± 0.98 9.62 ± 1.93 Data are presented as the mean ± standard deviation lncRNA CTBP1-AS overexpression affects follicular development by disturbing with the function of GCs To investigate the effect of lncRNA CTBP1-AS on granulosa cell function, we overexpressed lncRNA CTBP1-AS in KGN cells and detected changes in cell growth, apoptosis, cell cycle, cell migration, and other functions. The proliferation of KGN cells was detected by CCK-8, and it was found that compared with WT and NC, the cell proliferation ability of KGN cells overexpressed lncRNA CTBP1-AS was reduced, but the difference was not yet statistically significant (Fig. 2 C). The results of flow cytometry indicated that the difference in the proportion of the number of cells at each time image of the cell cycle in the G0-G1, S, and G2-M phases of KGN cells overexpressed lncRNA CTBP1-AS was not statistically significant (Table 6 , Fig. 3 A-B), suggesting that overexpression of lncRNA CTBP1-AS did not affect the cell cycle of KGN cells. In addition, flow cytometry was used to examine the effect of lncRNA CTBP1-AS overexpression on KGN cell apoptosis, and the results showed that the proportion of late apoptotic cells was increased in KGN cells overexpressed lncRNA CTBP1-AS as compared to WT and NC (Fig. 3 C-D), which suggests that overexpression of lncRNA CTBP1-AS promotes apoptosis in KGN cells. Cell scratch wound assay and Transwell assay were used to investigate the effect of lncRNA CTBP1-AS on the cell migration profile. The results of cell scratch wound assay revealed that the migration ability of KGN cells was significantly decreased after overexpression of lncRNA CTBP1-AS (Fig. 4A-B); Transwell assay illustrated that overexpression of lncRNA CTBP1- AS was detrimental to cell migration (Fig. 5 A-E). Both experimental results suggested that overexpression of lncRNA CTBP1-AS was unfavorable to cell migration. Discussion In this randomized clinical study, we analyzed the expression levels of lncRNA CTBP1-AS in peripheral blood mononuclear cells and ovarian granulosa cells of PCOS patients and controls who met the inclusion criteria, and found that the expression levels of lncRNA CTBP1-AS in peripheral blood mononuclear cells and ovarian granulosa cells were significantly higher in the PCOS group compared with that in the normal control group. This suggests that the high expression of lncRNA CTBP1-AS may be related to the pathogenesis of PCOS, and is a potential diagnostic marker and drug treatment target. Liu [ 14 ] first reported that lncRNA CTBP1-AS expressed at elevated levels in peripheral blood mononuclear cells of PCOS patients and that abnormal expression of lncRNA CTBP1-AS was a risk factor for PCOS. A case-control study involving Kashmiri women also found that subjects with higher levels of lncRNA CTBP1-AS expression had a significantly higher risk of PCOS (OR = 11.36, 95% CI = 5.59–23.08, P < 0.001), and that high lncRNA CTBP1-AS expression is a risk factor for PCOS in Kashmiri women [ 6 ] . In our study, we found that the average lncRNA CTBP1-AS level in peripheral blood mononuclear cells of patients with PCOS was higher than that of controls. lncRNA CTBP1-AS may be involved in the central part of the pathogenesis of PCOS through certain pathways, and there was a correlation between the expression level of lncRNA CTBP1-AS and the level of androgen and sinusoidal follicles, suggesting that lncRNA CTBP1 -AS may be associated with abnormal follicular development and hyperandrogenemia in PCOS. lncRNA CTBP1-AS was initially identified by investigators as a novel androgen receptor regulator [ 15 , 16 ] , indicating that lncRNA CTBP1-AS is associated with the clinical features of hyperandrogenism in PCOS. lncRNA CTBP1-AS expression is commonly upregulated in prostate cancer, and lncRNA CTBP1-AS promotes hormone-dependent and desmoplasia-resistant tumor growth. Mechanistically, lncRNA CTBP1-AS directly inhibits lncRNA CTBP1 expression by recruiting RNA-binding transcriptional repressors (PSFs) and histone deacetylases; lncRNA CTBP1-AS also suppresses tumor suppressor genes and promotes cell cycle progression through PSF-dependent mechanisms, thus exhibiting overall androgen-dependent functions [ 11 , 17 ] . These studies initially demonstrated the possible relevance of lncRNA CTBP1-AS to PCOS, and its biological function and potential molecular mechanisms need to be further explored. Jin [ 18 ] applied high-density microarray technology to study differentially expressed lncRNAs in ovarian granulosa cells from PCOS patients (n = 4), and screening revealed that lncRNA CTBP1-AS expression was up-regulated in the PCOS-T group, by 1.3-fold and 1.5-fold, as respectively compared with the control and PCOS-N groups. A total of 30 follicular fluid specimens were collected in our study, and the average expression level of granulosa cells was higher in PCOS patients than in the control group, and the granulosa cell lncRNA CTBP1-AS level was positively correlated with the menstrual cycle. The length of the menstrual cycle mainly depends on the time frame of the follicular phase. Ovarian granulosa cells (GCs) exist in a proliferative manner in developing follicles and undergo multiple biochemical processes during folliculogenesis. In developing follicles, GCs communicate bi-directionally with oocytes through gap junctions [ 19 ] . Numerous studies have reported that the survival and physiological status of granulosa cells can have an impact on follicular development [ 20 , 21 ] . High levels of lncRNA CTBP1-AS may have affected the function of ovarian granulosa cells, leading to abnormal follicular development and prolonged follicular phase, which in turn caused menstrual abnormalities in PCOS. A study found that CTBP1-AS interacts with Polycomb histone (enhancer of zeste homolog 2 and embryonic (eZH2) and ectoderm development protein (eed)) in ovarian granulosa cells to regulate PCOS, and cryptotanshinone can reduce the expression level of CTBP1-AS in granulosa cells, which may be a new direction for PCOS treatment [ 22 ] . lncRNA CTBP1-AS overexpression may be involved in the pathogenesis of PCOS by affecting the function of ovarian granulosa cells. Numerous studies have revealed that the survival and physiological status of granulosa cells can affect follicular development and oocyte quality, and that rapid apoptosis of granulosa cells may lead to follicular dysfunction and follicular atresia, as well as a significant reduction in the maturation rate of the oocyte and oocyte developmental potential. On the other hand, enhancing granulosa cell activity and intracellular expression of related genes may improve oocyte quality to a certain extent and promote embryonic development potential [ 23 – 25 ] . In our study, we found that the proportion of apoptotic cells in granulosa cells was increased after overexpression of lncRNA CTBP1-AS , especially the proportion of apoptotic cells in the late stage was significantly increased, which is consistent with the findings of increased apoptosis of granulosa cells in PCOS patients [ 26 ] . Furthermore, we found that the migratory ability of granulosa cells was significantly decreased after overexpression of the lncRNA CTBP1-AS , and hypothesized that it might be involved in the mechanism related to ovulation disorder in PCOS. Normally, the process of ovulation is a process in which the oocyte is expelled together with its surrounding granulosa cells that form the oval corpuscle complex. Before ovulation, ovarian mound expansion occurs after mucoidization of the granulosa cells of the ovarian mound. If the expansion of the mound is impaired, it will lead to abnormal ovulation [ 27 ] . Consequently, the reduced migratory capacity of granulosa cells may cause abnormal mound expansion and abnormal follicular migration to the ovarian surface, which in turn leads to impaired ovulation in PCOS and increases the incidence of its unruptured follicular luteinization syndrome. In the microenvironment of the ovary, there are other complex mechanisms for the regulation of ovulation, such as the regulatory role between steroid hormones, prostaglandins, proteolytic enzymes, and other cytokines. We still need to conduct more exploratory studies to elucidate and validate this hypothesis. In conclusion, granulosa cells overexpressing lncRNA CTBP1-AS exhibited an increased proportion of apoptotic cells and a significant decrease in migration ability, and the corresponding functional alterations in ovarian granulosa cells provide a positive experimental basis for elucidating the mechanism of action of PCOS development. Conclusion lncRNA CTBP1-AS may affect the function of human ovarian granulosa cells, resulting in an increase in apoptosis and a decrease in migration capacity, which causes impaired follicular development, ovulation disorders, and hyperandrogenemia in PCOS. However, the exact molecular genetic mechanism still needs to be further investigated. Declarations Data availability The datasets generated or analyzed in the current study will be available upon reasonable request. Funding This study was financially supported by the 2019 Natural Science Foundation of Guangxi, China (No. 2019GXNSFBA245020), the High-Level Talent Scientific Research Project of the Affiliated Hospital of Youjiang Medical University for Nationalities, China (No. Y20196316), and Self-financed scientific research projects of Guangxi Autonomous Region Health and Wellness Commission (NO.Z-L20230901). Acknowledgements Not applicable. Patient consent for publication All the patients in this project signed the consent forms. Conflict of Interest The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. Author contributions L Q, and C T contributed to the study design and data acquisition, drafted the manuscript, and were the co-first authors. L H, X Q, S L, B H, J W, and L L contributed to contributed experimental data. X L is considered a correspondence author. All authors have read and approved the final manuscript. Ethics approval and consent to participate The present study was approved by the ethics committee of The Affiliated Hospital of Youjiang Medical University for Nationalities (Guangxi, China; approval no. YYFY-LL-2022-61); all subjects provided signed consent forms prior to recruitment to the study. References Herman R, Sikonja J, Jensterle M, et al. Insulin metabolism in polycystic ovary syndrome: secretion, signaling, and clearance[J]. International Journal of Molecular Sciences, 2023, 24(4): 3140. DOI:10.3390/ijms24043140. Sadeghi H M, Adeli I, Calina D, et al. Polycystic ovary syndrome: a comprehensive review of pathogenesis, management, and drug repurposing[J]. International Journal of Molecular Sciences, 2022, 23(2): 583. DOI:10.3390/ijms23020583. Szukiewicz D, Trojanowski S, Kociszewska A, et al. Modulation of the inflammatory response in polycystic ovary syndrome (pcos)—searching for epigenetic factors[J]. 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Analysis of the androgen receptor–regulated lncrna landscape identifies a role for arlnc1 in prostate cancer progression[J]. Nature Genetics, 2018, 50(6): 814–824. DOI:10.1038/s41588-018-0120-1. Takayama K, Horie-Inoue K, Katayama S, et al. Androgen-responsive long noncoding rna ctbp1-as promotes prostate cancer[J]. The EMBO Journal, 2013, 32(12): 1665–1680. DOI:10.1038/emboj.2013.99. Jin L, Yang Q, Zhou C, et al. Profiles for long non-coding rnas in ovarian granulosa cells from women with pcos with or without hyperandrogenism[J]. Reproductive Biomedicine Online, 2018, 37(5): 613–623. DOI:10.1016/j.rbmo.2018.08.005. Jozkowiak M, Hutchings G, Jankowski M, et al. The stemness of human ovarian granulosa cells and the role of resveratrol in the differentiation of mscs-a review based on cellular and molecular knowledge[J]. Cells, 2020, 9(6): 1418. DOI:10.3390/cells9061418. Brązert M, Iżycki D, Kranc W, et al. Genes involved in hormone metabolism and cellular response in human ovarian granulosa cells[J]. Journal of Biological Regulators and Homeostatic Agents, 2019, 33(2): 461–468. Zhu G, Fang C, Li J, et al. Transcriptomic diversification of granulosa cells during follicular development in chicken[J]. Scientific Reports, 2019, 9(1): 5462. DOI:10.1038/s41598-019-41132-1. Wen M, Dou X, Zhang S, et al. CTBP1‑AS upregulation is associated with polycystic ovary syndrome and can be effectively downregulated by cryptotanshinone[J]. Molecular Medicine Reports, 2022, 26(1): 245. DOI:10.3892/mmr.2022.12761. Shen Q, Liu Y, Li H, et al. Effect of mitophagy in oocytes and granulosa cells on oocyte quality†[J]. Biology of Reproduction, 2021, 104(2): 294–304. DOI:10.1093/biolre/ioaa194. Xing J, Qiao G, Luo X, et al. Ferredoxin 1 regulates granulosa cell apoptosis and autophagy in polycystic ovary syndrome[J]. Clinical Science (London, England: 1979), 2023, 137(6): 453–468. DOI:10.1042/CS20220408. Liu S, Jia Y, Meng S, et al. Mechanisms of and potential medications for oxidative stress in ovarian granulosa cells: a review[J]. International Journal of Molecular Sciences, 2023, 24(11): 9205. DOI:10.3390/ijms24119205. Gong Y, Luo S, Fan P, et al. Growth hormone activates pi3k/akt signaling and inhibits ros accumulation and apoptosis in granulosa cells of patients with polycystic ovary syndrome[J]. Reproductive biology and endocrinology: RB&E, 2020, 18(1): 121. DOI:10.1186/s12958-020-00677-x. Li Y, Wang H, Zhou D, et al. Up-regulation of long noncoding rna sra promotes cell growth, inhibits cell apoptosis, and induces secretion of estradiol and progesterone in ovarian granular cells of mice[J]. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research, 2018, 24: 2384–2390. DOI:10.12659/msm.907138. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Dec, 2024 Read the published version in Journal of Ovarian Research → Version 1 posted Editorial decision: Revision requested 17 Nov, 2024 Reviews received at journal 17 Nov, 2024 Reviews received at journal 15 Nov, 2024 Reviewers agreed at journal 06 Nov, 2024 Reviewers agreed at journal 03 Nov, 2024 Reviewers agreed at journal 16 Oct, 2024 Reviewers invited by journal 14 Oct, 2024 Editor assigned by journal 14 Oct, 2024 Submission checks completed at journal 14 Oct, 2024 First submitted to journal 12 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5252234","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":379135773,"identity":"2ae435c1-6106-4792-92ad-d420ef0b1774","order_by":0,"name":"Li Qin","email":"","orcid":"","institution":"The Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Qin","suffix":""},{"id":379135775,"identity":"694638a6-a8d5-4fdd-8674-fdbdba13d744","order_by":1,"name":"Chun Tian","email":"","orcid":"","institution":"The Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Chun","middleName":"","lastName":"Tian","suffix":""},{"id":379135777,"identity":"60644ac0-65d2-491e-8b86-195a6070b95f","order_by":2,"name":"Liying Huang","email":"","orcid":"","institution":"The Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Liying","middleName":"","lastName":"Huang","suffix":""},{"id":379135778,"identity":"a18fe905-92f0-4fb6-9e80-c08c5b2aff8f","order_by":3,"name":"Xiao Qin","email":"","orcid":"","institution":"The Southwest Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Qin","suffix":""},{"id":379135779,"identity":"1b23e16a-59bd-4914-8708-cbb35961d35c","order_by":4,"name":"Shaohua Ling","email":"","orcid":"","institution":"The Southwest Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Shaohua","middleName":"","lastName":"Ling","suffix":""},{"id":379135780,"identity":"cbf175c5-d3f2-425f-992f-c932a6e2fd52","order_by":5,"name":"Jingxi Wei","email":"","orcid":"","institution":"The Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Jingxi","middleName":"","lastName":"Wei","suffix":""},{"id":379135781,"identity":"9fde0582-400d-471f-84e8-f44299fb4142","order_by":6,"name":"Bingsheng Huang","email":"","orcid":"","institution":"The Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Bingsheng","middleName":"","lastName":"Huang","suffix":""},{"id":379135783,"identity":"5f47aa6c-f241-4b1e-8e63-173e5fa2874e","order_by":7,"name":"Lining Li","email":"","orcid":"","institution":"The Southwest Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Lining","middleName":"","lastName":"Li","suffix":""},{"id":379135784,"identity":"6fb11009-7a48-4442-9f31-e64e0320d6e1","order_by":8,"name":"Xiaoqiong Luo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAq0lEQVRIiWNgGAWjYJACZsYGGx5+9gbStKTJSPYcIE3LYRuDGw5EKjdn7z38unDHeR6GGwyMHz7mEKHFsudcmvXMM7d5GGc3MEvO3EaEFoMbOWbGvG23eZhlDrAx85Kg5RwPm0QC8VqMH/O2HeDhIV7LmTNmzDPPJPNI8BxsJtIvx3uMPxfusLO3P9588MNHYrQAAZsEhGZsIE49EDB/IFrpKBgFo2AUjEwAAGC+NXkUUZLoAAAAAElFTkSuQmCC","orcid":"","institution":"The Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":true,"prefix":"","firstName":"Xiaoqiong","middleName":"","lastName":"Luo","suffix":""}],"badges":[],"createdAt":"2024-10-12 15:38:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5252234/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5252234/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13048-024-01571-5","type":"published","date":"2024-12-19T15:57:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":70208903,"identity":"47f1ef8b-664e-443b-891b-d00bbc36a9f3","added_by":"auto","created_at":"2024-11-29 14:09:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":144246,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression level of lncRNA CTBP1-AS significantly increased in patients with PCOS. (A) Relative expression levels of lncRNA CTBP1-AS in peripheral blood mononuclear cells of the control and PCOS groups. (B) Relative expression of lncRNA CTBP1-AS in peripheral blood mononuclear cells across PCOS subtypes. (C) Relative expression of lncRNA CTBP1-AS in peripheral blood mononuclear cells based on subgroup clinical characteristics. (D) Relative expression of lncRNA CTBP1-AS in granulosa cells from the control and PCOS groups.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5252234/v1/a273498f708d6dcc4ca7de24.png"},{"id":70208906,"identity":"3d7e4718-a8f8-42ad-85e3-6d90ab56dcb6","added_by":"auto","created_at":"2024-11-29 14:09:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":529054,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of overexpression of lncRNA CTBP1-AS on the proliferative function of KGN cells. (A) KGN cells were infected by adenovirus for 48h. (B) The expression level of lncRNA CTBP1-AS in KGN cells were detected by RT-qPCR. (C) Cell viability was detected by CCK-8 assay in the Negative Control (NC), Wild Type (WT) without virus, and Overexpression of lncRNA CTBP1-AS (Over Expression (OE)) groups.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5252234/v1/cd622a4f0fd33f20f3cd30c4.png"},{"id":70208907,"identity":"2d011e84-8673-4778-97aa-53258e56eb48","added_by":"auto","created_at":"2024-11-29 14:09:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":243775,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of overexpression of lncRNA CTBP1-AS on cell cycle and apoptosis in KGN cells. (A-B) The cell cycle of KGN cells in NC, WT and OE groups was detected by flow cytometry and visualized using bar graphs. (C-D) Flow cytometry assays showed apoptosis levels in each group and were visualized using bar graphs.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5252234/v1/dad43ce8a0d810cf92ad7708.png"},{"id":70209280,"identity":"bf689f06-75a6-4926-80c1-5bad3b568b48","added_by":"auto","created_at":"2024-11-29 14:17:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4202696,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5252234/v1/f8051bab3deac3030e771787.png"},{"id":70209279,"identity":"34b44c12-ac19-4d49-b871-d228c2475cb5","added_by":"auto","created_at":"2024-11-29 14:17:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1649152,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of overexpression of lncRNA CTBP1-AS on cell migration in KGN cells. (A-D) Transwell cell migration assay showed migratory ability in NC, WT and OE groups and were visualized using bar graphs.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5252234/v1/9ba116430cb34b29812d444b.png"},{"id":72201706,"identity":"f4de877a-6808-4b42-bd62-048a59193501","added_by":"auto","created_at":"2024-12-23 16:10:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9191797,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5252234/v1/d4eaea4c-8c96-4bba-a55f-59471d3f0a3d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eClinical significance and biological roles of lncRNA CTBP1-AS in Polycystic Ovary Syndrome\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePolycystic ovary syndrome (PCOS), a common heterogeneous endocrine and metabolic disorder, is one of the most common reproductive endocrine disorders in women of childbearing age, affecting up to 20% of women worldwide\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. The etiology and pathogenesis of PCOS are complex and influenced by environmental, psychological, and genetic factors, but the exact etiology has not yet been identified\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. The clinical manifestations of PCOS are highly heterogeneous, and there is no specific treatment in the clinic. For women of childbearing age, the main treatment is ovulation promotion and assisted reproduction techniques, and for women who have no requirement for childbearing, the prevention and treatment of long-term complications and metabolic syndrome should also be carried out, and such metabolic and endocrine disorders may affect the whole life of a woman\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Therefore, the diagnosis and treatment of PCOS still need to be further researched into its pathogenesis-related factors and progression mechanisms, to identify new diagnostic and therapeutic targets, provide early diagnosis of PCOS patients, and provide new and better individualized diagnostic and therapeutic methods.\u003c/p\u003e \u003cp\u003eLong noncoding RNA of C-Terminal binding protein 1 antisense (lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e) is a newly discovered long noncoding RNA\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e, a potential androgen receptor regulator, functions in the androgen receptor (AR) signaling pathway \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Aberrant expression of AR can lead to enhanced activation of otherwise normal levels of androgens (testosterone and dihydrotestosterone) in the body, resulting in hyperandrogenemia\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. The available evidence suggests that metabolic disturbances due to hyperandrogenemia are one of the important features of the pathological changes in PCOS\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. The lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e as a new androgen-regulated long noncoding RNA has gradually attracted the attention of many scholars\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Previous studies have found that lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e is associated with the development of PCOS, but their study samples are small and still need to expand the sample size for further studies. Previous studies have found that lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e is associated with the pathogenesis of PCOS, but their samples are small and limited to the detection of a single type of cell in patients with PCOS. The influence of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e on the occurrence and development of PCOS as well as a clear mechanism of action still requires further study\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur study aimed to further explore the correlation between lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e and the pathogenesis of PCOS by expanding the sample size and investigate the functional effects of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e on ovarian GCs by cellular assays. This study confirmed the functional role of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in the occurrence and development of PCOS, and explored new targets for molecular diagnosis and gene therapy of PCOS.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eIn this study, a case-control study was used, and patients who visited the Reproductive Medicine Center of the Affiliated Hospital of Youjiang Medical University for Nationalities in Guangxi from January 2018 to March 2019 were selected for the study. Patients with polycystic ovary syndrome served as the case group, and age-matched patients who underwent assisted reproductive technology for fertilization due to tubal factors or male factors were selected as the control group. (1) A total of 125 peripheral blood specimens were collected, including 85 cases in the case group and 40 cases in the control group; the mean age was 27.38\u0026thinsp;\u0026plusmn;\u0026thinsp;4.35 years. Inclusion criteria were as follows: 1) Case group: The diagnostic criteria for PCOS were based on the Rotterdam criteria recommended by ESHRE/ASRM in 2003: 1) oligo-ovulation and/or anovulation (OA); 2) increased serum androgen levels and/or hyperandrogenism (HA); 3) polycystic ovarian changes. The presence of two of the above three items at the same time needs to rule out other diseases, such as Cushing syndrome, congenital adrenal hyperplasia, and other diseases causing high androgen, as well as hyperprolactinemia and other diseases causing abnormal ovulation. ②Control group: patients with infertility due to tubal or male factors, regular menstruation (menstrual cycle of 28\u0026thinsp;\u0026plusmn;\u0026thinsp;7 days), no clinical signs of hyperandrogenism, normal ovulation by ultrasound monitoring, and normal morphology of both ovaries during the same period. (2) A total of 30 follicular fluid specimens were collected, 13 in the case group and 17 in the control group; the mean age was 32.87\u0026thinsp;\u0026plusmn;\u0026thinsp;4.15 years. The inclusion criteria were as follows: ① Case group: patients with PCOS who underwent in vitro fertilization and embryo transfer (IVF-ET) for the first time due to female factor (diagnostic criteria as before). ②Control group: patients who underwent IVF-ET for the first time due to tubal factor infertility, with regular menstruation, no clinical manifestations of hyperandrogenism, and no abnormality in the morphology of bilateral ovaries under ultrasound.\u003c/p\u003e \u003cp\u003eAll subjects included in the study were excluded from a history of ovarian surgery or radiotherapy, endometriosis, uterine fibroids, endometrial polyps, uterine malformations, uterine adhesions, history of pelvic tuberculosis, systemic diseases, and hereditary diseases, and there was no history of hormonal medications in the last 3 months, and other preoperative physical examinations showed no significant abnormalities. The study subjects had complete clinical information, and no significant difference was observed in the age composition ratio of each group (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The study protocol was approved by the Ethics Committee of the hospital, and specimens were collected after the subjects themselves signed informed consent.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical indicators of peripheral blood samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCOS (N\u0026thinsp;=\u0026thinsp;85)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl(N\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et / Z\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26(24,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(24, 31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of infertility (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(1, 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(1, 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual cycles(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(60, 90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(30, 40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntral follicle count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(28, 40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(15, 20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic sex hormone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFSH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.67(5.53, 12.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.16(3.64, 5.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.0(45.0, 68.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.0(38.0, 59.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.46(0.30, 0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49(0.22, 0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.613\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRL (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.58\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.80\u0026thinsp;\u0026plusmn;\u0026thinsp;4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.55(5.00,10.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.48(2.37, 6.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.87(4.60, 5.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.75(4.52, 5.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFINS (pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.0(58.1, 89.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.0(40.5, 68.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMAIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.44(1.77, 2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57(1.26, 2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.7(20.1, 24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.3(19.1, 24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, or median (interquartile range). FSH, follicle-stimulating hormone; LH, luteinizing hormone; E2, estradiol; P, progestogens; T, testosterone; PRL, prolactin; AMH, anti-mullerian hormone; FPG, Fasting Plasma Glucose; FINS, Fasting Insulin; HOMA-IR, homeostatic model assessment of insulin resistance; BMI, body mass index; *P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a statistically significant association between the variables.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCell culture and cell transfection\u003c/h3\u003e\n\u003cp\u003eHuman ovarian granulosa cells KGN were purchased from the Cell Bank of the Chinese Academy of Sciences. Cells were cultured in Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium (DMEM) containing 10% fetal bovine serum (Ausgenex), penicillin (100 U/mL, Solarbio), and puromycin (100 \u0026micro;g/mL, Thermofisher). 293A and 293T cells were purchased from the Cell Bank of the Chinese Academy of Sciences, and the lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e overexpression plasmid was purchased from Suzhou Ltd. Adenovirus after successful packaging were transfected into the cultured KGN cells at Polybrene 4 \u0026micro;g/ml, MOI\u0026thinsp;=\u0026thinsp;5 conditions, and the fluorescence expression was observed 48\u0026ndash;72 hours after infection.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical indicators of granulocyte samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCOS (N\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl(N\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et / Z\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.92\u0026thinsp;\u0026plusmn;\u0026thinsp;4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.59\u0026thinsp;\u0026plusmn;\u0026thinsp;3.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of infertility (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(2, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(2,4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual cycles(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60(37, 90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(30, 33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntral follicle count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(19,30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(11, 16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic sex hormone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFSH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.70(5.1, 6.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.68(5.09, 8.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.43(2.75, 11.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.60(2.71, 4.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.31\u0026thinsp;\u0026plusmn;\u0026thinsp;12.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.18\u0026thinsp;\u0026plusmn;\u0026thinsp;22.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRL (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.37(8.63,13.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.3(9.99,17.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.12\u0026thinsp;\u0026plusmn;\u0026thinsp;3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.05(4.58, 5.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.80(4.60, 5.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFINS (pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.92\u0026thinsp;\u0026plusmn;\u0026thinsp;10.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.01\u0026thinsp;\u0026plusmn;\u0026thinsp;15.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMAIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.95\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a statistically significant association between the variables.\u003c/p\u003e\n\u003ch3\u003eCCK-8 assa\u003c/h3\u003e\n\u003cp\u003eCCK-8 assay was used to measure cell proliferation. In the presence of 1-Methoxy PMS, WST-8 in the reagent was reduced by dehydrogenases in the cells to a highly water-soluble yellow formazan product (Formazan dye). The number of produced formazan products was proportional to the number of living cells. The OD value of the optical density at 450 nm, measured using an enzyme marker, reflected the change in the number of living cells, thus detecting differences in proliferation produced by different cells over time.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eFlow cytometry\u003c/h3\u003e\n\u003cp\u003eThe cells were digested and centrifuged at 200 g. The supernatant was discarded. The cells were resuspended with 50 \u0026micro;L 1\u0026times; Binding Buffer, and the dyes were added according to the following groups: without any dye (negative control), 5 \u0026micro;L Annexin V-APC (single positive control), 10\u0026micro;L 7-AAD (single positive control), 5 \u0026micro;L Annexin V-FITC and 10 \u0026micro;L PI (sample tube). The mixture was incubated for 15 minutes in the dark. The apoptosis rate was analyzed by flow cytometer (BD Biosciences).\u003c/p\u003e\n\u003ch3\u003eCell scratching assay\u003c/h3\u003e\n\u003cp\u003eCells were seeded in transwell chambers, and the chambers were immersed in 2% serum medium outside the chambers. 24 hours later, the chambers were removed, and the cells flanking the outside of the chambers were stained and photographed with a light microscope.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between lncRNA CTBP1-AS expression levels in peripheral blood mononuclear cell and clinical parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClinical indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eExpression of lncRNA CTBP1-AS(N\u0026thinsp;=\u0026thinsp;125)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of infertility (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.328\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual cycles(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntral follicle count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.030*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic sex hormone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFSH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.537\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.024*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRL (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFINS (pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.332\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMAIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a statistically significant association between the variables.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eReverse transcription quantitative polymerase chain reaction (RT-qPCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted by using AxyPrep Total RNA Small Volume Preparation Kit, and the extracted RNA was detected by applying a nucleic acid quantifier, including the content and purity. The RNA with qualified purity and concentration was subjected to reverse transcription using the Reverse Transcription Reaction Kit (Fermentas Inc., USA). Then, lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e and the internal reference GAPDH were amplified by PCR, and a sample from the same normal group was added as a reference sample for each RT-qPCR. The reaction system for RT-qPCR was 20 \u0026micro;l, consisting of 3 \u0026micro;l F, 3 \u0026micro;l R, 3 \u0026micro;l DEPC, 1 \u0026micro;l cDNA and 10 \u0026micro;l SYBR. The reaction conditions were: 95 ℃ for 10 min pre-denaturation followed by 95 ℃ for 15 s and 60 ℃ for 1 min for 40 cycles. Three replicate measurements were taken for each sample to ensure accurate results. The Ct mean values of each sample lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e and GAPDH were first calculated separately, and then the data were used to calculate the relative quantity (RQ) of expression using the 2-ΔΔCT method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eSPSS 13.0 software was used for statistical processing. Measurement data conforming to normal distribution were expressed as \u0026oline;x\u0026thinsp;\u0026plusmn;\u0026thinsp;s, and comparison of data between groups should be made by t-test or ANOVA according to the nature of the data; if they did not conform to normal distribution they were expressed as median (M) and quartiles (P\u003csub\u003e25\u003c/sub\u003e, P\u003csub\u003e75\u003c/sub\u003e), and comparison between groups was changed to rank sum test. Count data were expressed as rates (%), and comparisons between groups were made using the four-cell χ\u003csup\u003e2\u003c/sup\u003e test or Fischer\u0026rsquo;s exact test. Correlations between variables were analyzed by Pearson or Spearman's rank correlation analysis, multiple linear regression analysis. A value of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGeneral clinical information\u003c/h2\u003e \u003cp\u003eIn the clinical data of peripheral blood samples, age, duration of infertility, basal FSH, P, PRL, FPG, and BMI levels of two study groups were compared and the differences were not statistically significant. The menstrual cycle, antral follicle count, basal LH, E2, T, AMH, FINS, and HOMAIR levels were higher in the PCOS group than in the control group, and the difference was statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the clinical data of granulocyte samples, age, duration of infertility, and BMI level of the two study\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between lncRNA CTBP1-AS expression levels in in GCs and clinical parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClinical indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eExpression of lncRNA CTBP1-AS(N\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.045*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of infertility (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual cycles(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntral follicle count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic sex hormone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFSH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLH (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRL (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.595\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFINS (pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMAIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a statistically significant association between the variables.\u003c/p\u003e \u003cp\u003egroups were compared and the difference was also not statistically significant. After pretreatment of the study subjects who entered the IVF-ET cycle, the differences in basal FSH, LH, E2, PRL, P, and T were not statistically significant when comparing the pre-superovulation sex hormone levels between the two groups. FPG, FINS, and HOMAIR in the PCOS group were higher than those in the control group, but the difference was not statistically significant. It suggested the two groups were more balanced in terms of sex hormones and other indicators at the time of entry into the treatment cycle, and the follow-up studies were comparable. The menstrual cycle, antral follicle count, and AMH were higher in the PCOS group than in the control group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe expression of lncRNA\u003c/b\u003e \u003cb\u003eCTBP1-AS\u003c/b\u003e \u003cb\u003ein peripheral blood mononuclear cells and follicular fluid GCs\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn our study, we found that patients with PCOS had a higher lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e level in peripheral blood mononuclear cells, compared with controls(0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43 vs. 0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29, P\u0026thinsp;=\u0026thinsp;0.034) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). To better study the clinical heterogeneity of PCOS, we further divided the PCOS group into several subgroups according to the Rotterdam criteria and the main clinical characteristics (hyperandrogenemia and insulin resistance), respectively, and analyzed them statistically using the control group as a reference. They were categorized into 4 subtypes according to the Rotterdam criteria: complete OA\u0026thinsp;+\u0026thinsp;HA\u0026thinsp;+\u0026thinsp;PCO (n\u0026thinsp;=\u0026thinsp;33), ovulatory HA\u0026thinsp;+\u0026thinsp;PCO (n\u0026thinsp;=\u0026thinsp;4), non-hyperandrogenic OA\u0026thinsp;+\u0026thinsp;PCO (n\u0026thinsp;=\u0026thinsp;39), and classic OA\u0026thinsp;+\u0026thinsp;HA (n\u0026thinsp;=\u0026thinsp;9); Four subgroups were categorized according to the two main clinical features of hyperandrogenemia and insulin resistance: the hyperandrogenic group HA (n\u0026thinsp;=\u0026thinsp;36), the insulin-resistant group IR (n\u0026thinsp;=\u0026thinsp;14), the hyperandrogenic\u0026thinsp;+\u0026thinsp;insulin-resistant group HA\u0026thinsp;+\u0026thinsp;IR (n\u0026thinsp;=\u0026thinsp;10), and the no hyperandrogenic and insulin-resistant group NONE (n\u0026thinsp;=\u0026thinsp;25).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of follicular fluid granulosa cell lncRNA CTBP1-AS expression levels with IVF-ET indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClinical indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eExpression of lncRNA CTBP1-AS(N\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGn Days of use (d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Gn (IU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCG day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrium(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of oocytes retrieved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of MII oocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.of fertilized oocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of cleavage embryos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of good-quality embryos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a statistically significant association between the variables.\u003c/p\u003e \u003cp\u003eStatistical analysis of the four subtypes of the Rotterdam criteria for PCOS (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) revealed a statistically significant difference between the elevated expression of the lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in complete PCOS only compared with controls(1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47 vs. 0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29, P\u0026thinsp;=\u0026thinsp;0.001). In contrast, the expression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in ovulatory PCOS (0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38) and non-hyperandrogenic PCOS (0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40) was elevated compared with the control group, but the difference was not statistically significant; the expression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in classic PCOS (0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16 ) was not significantly different from the control group. Further two-by-two comparisons revealed that lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e expression in complete PCOS also differed from classic, non-hyperandrogenic PCOS and not from ovulatory PCOS.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStatistical analysis of the four subgroups with the main clinical features of PCOS (hyperandrogenemia and insulin resistance) versus the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) revealed that the expression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was elevated in the hyperandrogenemia group, and in the hyperandrogenemia\u0026thinsp;+\u0026thinsp;insulin resistance group, and the difference was statistically significant (0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41 vs. 0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29, P\u0026thinsp;=\u0026thinsp;0.031; 1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51 vs. 0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29, P\u0026thinsp;=\u0026thinsp;0.004); the mean expression level of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was also elevated in the non-hyperandrogenemia\u0026thinsp;+\u0026thinsp;insulin resistance group (0.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44) compared to the control group, but none of the differences were statistically significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05); in the insulin resistance group (0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31) the mean expression level of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was not significantly different from the control group. Further two-by-two comparisons revealed that the lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e expression in the hyperandrogenemia\u0026thinsp;+\u0026thinsp;insulin resistance group also differed from the insulin resistance group, the non-hyperandrogenemia\u0026thinsp;+\u0026thinsp;insulin resistance group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and did not differ from the hyperandrogenemia group.\u003c/p\u003e \u003cp\u003eThe mean expression level in GCs was higher in PCOS patients than in controls [0.39 (0.18, 0.66) vs. 0.17 (0.10, 0.34), P\u0026thinsp;=\u0026thinsp;0.043] (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe correlation between lncRNA\u003c/b\u003e \u003cb\u003eCTBP1-AS\u003c/b\u003e \u003cb\u003etranscript levels and clinical parameters\u003c/b\u003e\u003c/p\u003e \u003cp\u003ePearson or Spearman's rank correlation analysis was applied to analyze the correlation between lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e transcript levels and clinical parameters. The results showed that lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in peripheral blood mononuclear cells was correlated with sinus follicle number and androgen levels (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e); lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e transcript levels in GCs were negatively correlated with the age of the subjects and positively correlated with menstrual cycle; lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e levels in GCs were negatively correlated with the total amount of Gn in the subjects (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The results of the correlation analysis between granulosa cell lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e transcript levels and IVF parameters showed a negative correlation between lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e levels and the total amount of Gn in the subjects (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAdenovirus of lncRNA\u003c/b\u003e \u003cb\u003eCTBP1-AS\u003c/b\u003e \u003cb\u003eoverexpression infects ovarian granulosa cells\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe hypothesized that the lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e may be involved in the pathologic process of PCOS development by affecting the function of GCs and normal follicular development. To confirm the role of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in the pathogenesis of PCOS, lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e overexpression adenovirus was applied to infect KGN cells. According to the results of the pre-experiment, the optimal viral transfection conditions were obtained as Polybrene 4 \u0026micro;g/ml, MOI\u0026thinsp;=\u0026thinsp;5, and the infection efficiency reached more than 90% as seen under the inverted fluorescence microscope after 48h of transfection (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), which can be used for the subsequent cell function experiments. Total RNA was extracted from KGN cells after 48 hours of adenovirus infection, and the overexpression and silencing efficiencies were detected by RT- regulated more than 3000-fold in KGN cells that overexpressed the lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e (Over qPCR using empty virus (Negative Control, NC) and wild type KGN's cells not infected with the virus (Wild Type, WT) as a control, and the results showed that the expression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was up-\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eExpression, OE), whereas the difference in lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e expression between NC and WT was not statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe results of Cell Cycle\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCell Cycle(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG0-G1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e58.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e61.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e63.14\u0026thinsp;\u0026plusmn;\u0026thinsp;3.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e31.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e26.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e27.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG2-M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e9.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003elncRNA\u003c/b\u003e \u003cb\u003eCTBP1-AS\u003c/b\u003e \u003cb\u003eoverexpression affects follicular development by disturbing with the function of GCs\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo investigate the effect of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e on granulosa cell function, we overexpressed lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in KGN cells and detected changes in cell growth, apoptosis, cell cycle, cell migration, and other functions. The proliferation of KGN cells was detected by CCK-8, and it was found that compared with WT and NC, the cell proliferation ability of KGN cells overexpressed lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was reduced, but the difference was not yet statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The results of flow cytometry indicated that the difference in the proportion of the number of cells at each time image of the cell cycle in the G0-G1, S, and G2-M phases of KGN cells overexpressed lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was not statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B), suggesting that overexpression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e did not affect the cell cycle of KGN cells. In addition, flow cytometry was used to examine the effect of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e overexpression on KGN cell apoptosis, and the results showed that the proportion of late apoptotic cells was increased in KGN cells overexpressed lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e as compared to WT and NC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D), which suggests that overexpression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e promotes apoptosis in KGN cells. Cell scratch wound assay and Transwell assay were used to investigate the effect of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e on the cell migration profile. The results of cell scratch wound assay revealed that the migration ability of KGN cells was significantly decreased after overexpression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e (Fig.\u0026nbsp;4A-B); Transwell assay illustrated that overexpression of lncRNA CTBP1- AS was detrimental to cell migration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-E). Both experimental results suggested that overexpression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was unfavorable to cell migration.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this randomized clinical study, we analyzed the expression levels of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in peripheral blood mononuclear cells and ovarian granulosa cells of PCOS patients and controls who met the inclusion criteria, and found that the expression levels of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e in peripheral blood mononuclear cells and ovarian granulosa cells were significantly higher in the PCOS group compared with that in the normal control group. This suggests that the high expression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e may be related to the pathogenesis of PCOS, and is a potential diagnostic marker and drug treatment target.\u003c/p\u003e \u003cp\u003eLiu\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e first reported that lncRNA\u003cem\u003eCTBP1-AS\u003c/em\u003e expressed at elevated levels in peripheral blood mononuclear cells of PCOS patients and that abnormal expression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was a risk factor for PCOS. A case-control study involving Kashmiri women also found that subjects with higher levels of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e expression had a significantly higher risk of PCOS (OR\u0026thinsp;=\u0026thinsp;11.36, 95% CI\u0026thinsp;=\u0026thinsp;5.59\u0026ndash;23.08, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and that high lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e expression is a risk factor for PCOS in Kashmiri women\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In our study, we found that the average lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e level in peripheral blood mononuclear cells of patients with PCOS was higher than that of controls. lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e may be involved in the central part of the pathogenesis of PCOS through certain pathways, and there was a correlation between the expression level of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e and the level of androgen and sinusoidal follicles, suggesting that lncRNA CTBP1 -AS may be associated with abnormal follicular development and hyperandrogenemia in PCOS. lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was initially identified by investigators as a novel androgen receptor regulator\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, indicating that lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e is associated with the clinical features of hyperandrogenism in PCOS. lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e expression is commonly upregulated in prostate cancer, and lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e promotes hormone-dependent and desmoplasia-resistant tumor growth. Mechanistically, lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e directly inhibits lncRNA CTBP1 expression by recruiting RNA-binding transcriptional repressors (PSFs) and histone deacetylases; lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e also suppresses tumor suppressor genes and promotes cell cycle progression through PSF-dependent mechanisms, thus exhibiting overall androgen-dependent functions\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. These studies initially demonstrated the possible relevance of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e to PCOS, and its biological function and potential molecular mechanisms need to be further explored.\u003c/p\u003e \u003cp\u003eJin \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e applied high-density microarray technology to study differentially expressed lncRNAs in ovarian granulosa cells from PCOS patients (n\u0026thinsp;=\u0026thinsp;4), and screening revealed that lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e expression was up-regulated in the PCOS-T group, by 1.3-fold and 1.5-fold, as respectively compared with the control and PCOS-N groups. A total of 30 follicular fluid specimens were collected in our study, and the average expression level of granulosa cells was higher in PCOS patients than in the control group, and the granulosa cell lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e level was positively correlated with the menstrual cycle. The length of the menstrual cycle mainly depends on the time frame of the follicular phase. Ovarian granulosa cells (GCs) exist in a proliferative manner in developing follicles and undergo multiple biochemical processes during folliculogenesis. In developing follicles, GCs communicate bi-directionally with oocytes through gap junctions\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Numerous studies have reported that the survival and physiological status of granulosa cells can have an impact on follicular development\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. High levels of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e may have affected the function of ovarian granulosa cells, leading to abnormal follicular development and prolonged follicular phase, which in turn caused menstrual abnormalities in PCOS.\u003c/p\u003e \u003cp\u003eA study found that \u003cem\u003eCTBP1-AS\u003c/em\u003e interacts with Polycomb histone (enhancer of zeste homolog 2 and embryonic (eZH2) and ectoderm development protein (eed)) in ovarian granulosa cells to regulate PCOS, and cryptotanshinone can reduce the expression level of \u003cem\u003eCTBP1-AS\u003c/em\u003e in granulosa cells, which may be a new direction for PCOS treatment\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e overexpression may be involved in the pathogenesis of PCOS by affecting the function of ovarian granulosa cells. Numerous studies have revealed that the survival and physiological status of granulosa cells can affect follicular development and oocyte quality, and that rapid apoptosis of granulosa cells may lead to follicular dysfunction and follicular atresia, as well as a significant reduction in the maturation rate of the oocyte and oocyte developmental potential. On the other hand, enhancing granulosa cell activity and intracellular expression of related genes may improve oocyte quality to a certain extent and promote embryonic development potential\u003csup\u003e[\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. In our study, we found that the proportion of apoptotic cells in granulosa cells was increased after overexpression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e, especially the proportion of apoptotic cells in the late stage was significantly increased, which is consistent with the findings of increased apoptosis of granulosa cells in PCOS patients\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFurthermore, we found that the migratory ability of granulosa cells was significantly decreased after overexpression of the lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e, and hypothesized that it might be involved in the mechanism related to ovulation disorder in PCOS. Normally, the process of ovulation is a process in which the oocyte is expelled together with its surrounding granulosa cells that form the oval corpuscle complex. Before ovulation, ovarian mound expansion occurs after mucoidization of the granulosa cells of the ovarian mound. If the expansion of the mound is impaired, it will lead to abnormal ovulation\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Consequently, the reduced migratory capacity of granulosa cells may cause abnormal mound expansion and abnormal follicular migration to the ovarian surface, which in turn leads to impaired ovulation in PCOS and increases the incidence of its unruptured follicular luteinization syndrome. In the microenvironment of the ovary, there are other complex mechanisms for the regulation of ovulation, such as the regulatory role between steroid hormones, prostaglandins, proteolytic enzymes, and other cytokines. We still need to conduct more exploratory studies to elucidate and validate this hypothesis. In conclusion, granulosa cells overexpressing lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e exhibited an increased proportion of apoptotic cells and a significant decrease in migration ability, and the corresponding functional alterations in ovarian granulosa cells provide a positive experimental basis for elucidating the mechanism of action of PCOS development.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003elncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e may affect the function of human ovarian granulosa cells, resulting in an increase in apoptosis and a decrease in migration capacity, which causes impaired follicular development, ovulation disorders, and hyperandrogenemia in PCOS. However, the exact molecular genetic mechanism still needs to be further investigated.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated or analyzed in the current study will be available upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by the 2019 Natural Science Foundation of Guangxi, China (No. 2019GXNSFBA245020), the High-Level Talent Scientific Research Project of the Affiliated Hospital of Youjiang Medical University for Nationalities, China (No. Y20196316), and Self-financed scientific research projects of Guangxi Autonomous Region Health and Wellness Commission (NO.Z-L20230901).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the patients in this project signed the consent forms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL Q, and C T contributed to the study design and data acquisition, drafted the manuscript, and were the co-first authors. L H, X Q, S L, B H, J W, and L L contributed to contributed experimental data. X L is considered a correspondence author. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was approved by the ethics committee of The Affiliated Hospital of Youjiang Medical University for Nationalities (Guangxi, China; approval no. YYFY-LL-2022-61); all subjects provided signed consent forms prior to recruitment to the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHerman R, Sikonja J, Jensterle M, et al. Insulin metabolism in polycystic ovary syndrome: secretion, signaling, and clearance[J]. International Journal of Molecular Sciences, 2023, 24(4): 3140. DOI:10.3390/ijms24043140.\u003c/li\u003e\n \u003cli\u003eSadeghi H M, Adeli I, Calina D, et al. 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DOI:10.12659/msm.907138.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-ovarian-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jovr","sideBox":"Learn more about [Journal of Ovarian Research](http://ovarianresearch.biomedcentral.com)","snPcode":"13048","submissionUrl":"https://submission.nature.com/new-submission/13048/3","title":"Journal of Ovarian Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Polycystic ovary syndrome, lncRNA, CTBP1-AS, Expression regulation, Granulosa cells","lastPublishedDoi":"10.21203/rs.3.rs-5252234/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5252234/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePolycystic ovary syndrome (PCOS) is among the most prevalent endocrine and metabolic disorders affecting women of reproductive age. Multiple factors, including genetic predisposition, environmental influences, and lifestyle choices, are considered significant contributors to the development of PCOS. A kind of long noncoding RNA—C-Terminal binding protein 1 antisense (lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e) has been proven to be a new androgen receptor regulator. Previous studies showed that the lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003egene was highly expressed in a small sample of PCOS patients and was associated with the risk of PCOS, but its specific function and mechanism have not been clearly reported. In this study, the expression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003ewas detected by real-time quantitative PCR (RT-qPCR) in PCOS patients. In addition, lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e was overexpressed in KGN cells to explore its effect on granulocyte function. The results showed that the expression levels of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e were increased in serum single nucleated cells and follicular fluid granulosa cells of PCOS patients compared with controls, which correlated with androgen levels and sinus follicle number; overexpression of lncRNA \u003cem\u003eCTBP1-AS\u003c/em\u003e increased apoptosis and decreased cell migration ability, thus promoting the progression of PCOS. This study explores new biomarkers and therapeutic targets for the clinical individualised diagnosis and treatment of PCOS.\u003c/p\u003e","manuscriptTitle":"Clinical significance and biological roles of lncRNA CTBP1-AS in Polycystic Ovary Syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-29 14:09:35","doi":"10.21203/rs.3.rs-5252234/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-17T21:17:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-17T06:59:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-15T18:37:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"15739799094308873913870004493891815764","date":"2024-11-06T07:40:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132647800092264178764813946314354584209","date":"2024-11-03T19:55:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"17189547213284908370617910000190149002","date":"2024-10-16T13:11:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-15T00:41:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-14T23:54:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-14T04:13:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Ovarian Research","date":"2024-10-12T15:23:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-ovarian-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jovr","sideBox":"Learn more about [Journal of Ovarian Research](http://ovarianresearch.biomedcentral.com)","snPcode":"13048","submissionUrl":"https://submission.nature.com/new-submission/13048/3","title":"Journal of Ovarian Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8783499d-bf07-4214-b1c9-fc8a3cfd9e18","owner":[],"postedDate":"November 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:01:21+00:00","versionOfRecord":{"articleIdentity":"rs-5252234","link":"https://doi.org/10.1186/s13048-024-01571-5","journal":{"identity":"journal-of-ovarian-research","isVorOnly":false,"title":"Journal of Ovarian Research"},"publishedOn":"2024-12-19 15:57:21","publishedOnDateReadable":"December 19th, 2024"},"versionCreatedAt":"2024-11-29 14:09:35","video":"","vorDoi":"10.1186/s13048-024-01571-5","vorDoiUrl":"https://doi.org/10.1186/s13048-024-01571-5","workflowStages":[]},"version":"v1","identity":"rs-5252234","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5252234","identity":"rs-5252234","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}