Do noncoding RNAs genes modulate PI3K/AKT signaling pathway in Polycystic ovary syndrome

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Omar, Osama Ahmed, Maha Gomaa, Eman Faruk, Hanan Fouad, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2756899/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Aug, 2023 Read the published version in Molecular Biology Reports → Version 1 posted 5 You are reading this latest preprint version Abstract Background and aims: The PI3K protein kinase B (PI3K/Akt) signaling pathway has crucial roles in insulin signaling and other endocrine disorders. It is the purpose of this study to validate the association of PCOS with PI3K/AKT pathway target genes, miR486-5p, and miR483-5p as well as to evaluate the outcome of metformin on the pathogenesis of PCOS. Methods : This case-controlled study included 3 subject groups: twenty healthy females (control group), twenty PCOS females before treatment, and twenty PCOS females treated with metformin at a dose (500 mg 3 times per day for three months). The following gene expressions were assessed by real-time PCR: PI3K, AKT, ERK, GLUT4, miR486-5p, and miR483-5p in the whole blood. Result: There was a significant decrease in miR486-5p and miR483-5p in the PCOS group with a significant negative correlation between miR486-5p and PI3K and a significant negative correlation between miR483-5p and ERK. Metformin treatment resulted in significant elevation of the studied miRNAs, significant downregulation of PI3K/AKT target genes, and significant amelioration of the gonadotrophic hormonal imbalance and insulin resistance markers: fasting blood glucose, HBA1C, fasting insulin, and GLUT4 gene expression. Conclusions: miRNA486 and miRNA483 downregulation may contribute to the etiology of PCOS, influence glucose metabolism, and result in IR in PCOS. Metformin's upregulation of those miRNAs affects glucose metabolism by controlling the expression of GLUT4, ameliorates PCOS-related insulin resistance, and improves PCOS-related hormonal imbalance by controlling the PI3K/AKT signaling pathway. PCOS miRNA 486 miRNA 483 PI3K/AKT GLUT 4 Figures Figure 1 Figure 2 Figure 3 Figure 4 Highlights - PCOS is associated with multiple endocrine disorders and the most common cause is increased androgen level. -Many differentially expressed miRNAs(miR-486-5p and miR-483-5p) in PCOS women are involved in pathological insulin signaling processes, the disorder secretion of inflammatory factors, and hormones. -The most relevant genes involved in steroidogenesis, (miR-486-5p and miR-483-5p) and their controversial properties. PCOS is a complex genetic syndrome. the expression of the genes for PI3K/AKT signaling, including GLTU4, ERK, AKT, and serine/threonine kinase 1 plays a key role in the pathogenesis of PCOS. 1. Introduction Polycystic ovary syndrome (PCOS) is a multifactorial endocrine disorder. It is known to be associated with excess androgen, ovarian dysfunction, endocrine disruption, insulin resistance (IR), infertility, obesity, and metabolic disorders of glucose ( 1 ). PCOS is considered the most endocrinal illness in females of reproductive age ( 2 ). It affects approximately 4–18% of all females of childbearing age all over the world ( 3 ). In the presence of compensatory hyperinsulinemia, insulin resistance (IR) is associated with a reduction in liver sex hormone binding globulin (SHBG) production and an increase in ovarian/adrenal production of androgens. Elevated levels of insulin increase the secretion of GnRH, with subsequent disturbance of the action of LH and FSH, development of hyperandrogenism, and ovulatory dysfunction ( 4 ). The important reason for hyperandrogenism in females with PCOS is an upregulated expression of rate-limiting enzymes of steroidogenesis (cytochrome p450c17) 3β-hydroxysteroid dehydrogenase(3β-HSD) and 17β-hydroxysteroid dehydrogenase (17βHSD) enzymes in the theca cells of the ovaries ( 5 ). The Phosphoinositide 3-kinase (PI3K) protein family can be split into 3 types (I, II, and III) according to their substrate preference and structure. Class I is the most important one as it has an important effect on many pathological and physiological conditions. At the plasma membrane, PI3K is activated near its substrate. In addition to fibroblast growth factor, vascular endothelial growth factor (VEGF), and insulin, PI3K can be activated by several growth factors ( 6 ). PI3K-Akt signaling pathway stimulation by insulin; activation of insulin receptors, lead to increase insulin receptor substrates (IRS), which bind with PI3K which produces phosphoinositide triphosphate (PIP3). The PIP3 acts on phosphoinositide-dependent kinase 1 (PDK1), leading to the phosphorylation of the Akt protein. Activated Akt protein affects downstream molecules such as GLUT4; it influences glucose metabolism ( 7 ). miRNAs are the Master Maestro of the human genome. They play a pivotal role in the post-transcriptional modifications in many interacting signaling pathways in different oncological and non-oncological pathological states. miR486-5p and miR486-3p act as prognostic and diagnostic markers in many diseases such as insulin resistance, hypertension, osteoarthritis, and metabolic syndromes (MS). In Egyptian males, miR486-5p was found to be a prognostic factor for insulin resistance (IR), elevated blood pressure (BP), and PCOS ( 8 ). In addition, several pieces of evidence suggested the involvement of miR483 over-expression in some pathological non-oncologic conditions like cardiovascular diseases, DM, obesity, non-alcoholic fatty liver disease (NAFLD), systemic sclerosis, rheumatoid arthritis, and metabolic syndrome ( 9 ). The study aims to determine whether metformin affects gene expression of PI3K, AKT, ERK, GLUT4, miR486-5p, and miR483-5p as well as to assess the status of insulin resistance and hormonal imbalance associated with PCOS patients. 2. Method The study was conducted under the Declaration of Helsinki and approved by the Local Ethics Committee of Cairo University, Faculty of Medicine, and written informed consent from all females (IRB number(284). In this case-control study, 60 females aged 25 to 35 were studied at Cairo University's Faculty of Medicine, Unit of Biochemistry and Molecular Biology. During the period January 2022 to June 2022, participants were recruited from the Obstetrics and Gynecology department at Minia University, Egypt. PCOS patients diagnosed according to the revised 2003 consensus on diagnostic criteria and long-term health risks associated with PCOS were eligible ( 10 ). There are three criteria for diagnosing PCOS: Oligo ovulation indoor an-ovulation, clinical indoor biochemical evidence of hyperandrogenism, and polycystic ovarian morphology. The case must meet at least two of the three criteria to be classified as PCOS. Subjects of the study were subdivided into three groups: Group Ⅰ: included 20 age-matched females as a control group. Group Ⅱ: included 20 females of reproductive age with polycystic ovary syndrome without complication, and who did not receive any hormone drugs or oral contraceptives. Group Ⅲ: included 20 of the PCOS group who were treated with metformin at a dose (500 mg three times per day for 3 months). Exclusion criteria included: females in the postmenopausal phase and patients with any condition that causes hyperandrogenism, or hypothyroidism. Female patients with liver, kidney, and heart diseases were also excluded. The history of all eligible females was taken in detail, including age at the time of examination, disease duration, and types of drugs taken. In addition to measuring weight, height, and body mass index, a thorough clinical examination focused on endocrine gland disease. By local standards, routine laboratory investigations were conducted. 2.1. Sample collection: After signing written informed consent: Five mL venous blood samples were taken from all subjects using the BD Vacutainer system during the 3rd, 4 th , and 5th days of the menstrual cycle and at any time for those who had amenorrhea, (NB: two samples were collected from Group Ⅲ before and after metformin administration) kept at -80 °C until the time of analysis of the following parameters: Gene expression of PI3K/AKT downstream signaling target genes: extracellular signal-regulated kinase (ERK), serine/threonine kinase 1 (AKT), and GLUT4 in the peripheral blood by real-time PCR. Evaluation of miR486-5p and miR483-5p in peripheral blood by real-time PCR. 2.2. Molecular Biology Techniques: Assessment of expression levels of PI3K, AKT, ERK, GLUT 4, miR486-5p, and miR483-5p in the whole blood by real-time qRT PCR : 2.2.1.RNA extraction: RNA was isolated using miRNAs mini kit (Qiagen, Germany, Cat. No. 217004) permitting the manufacturer’s recommendations. 2.2.2. Quantitation of isolated RNAs: The absorbance of isolated miRNA was measured by Nanodrop® spectrophotometer at 260 nm. 2.2.3. Amplification and quantification of the genes using Reverse Transcription - Polymerase Chain Reaction (RT-PCR): Transcript ® Green One-Step qRT-PCR Super Mix kit (Transgenbiotech, China, Cat No. AQ211) was used permitting the manufacturer’s recommendations. 2.2.4. Primer selection: We obtained the primers for PCR from GenBank RNA sequences cited at http://www.ncbi.nlm.nih.gov/tools/primer-blast. When selecting the ideal primer pair, the following factors were considered: melting temperature (Tm: 60–650C), guanine, cytosine content (40%–60%), and amplicon length between 90 and 200 bp. Software version 3.1 of the StepOnePlus Real-Time PCR system (Applied Biosystems, USA) was used to examine gene expression. SYBR® Green (ThermoFisher, USA) was used to measure relative gene expression. A hardening temperature of 60◦C was adjusted for all primer sets. Real-time PCR was done in 25μL final volume containing SYBR Green master mix, 900 nmol/L of every PCR primer, and 3 μL of cDNA. Amplification conditions were done based on the manufacturer references: 2 min at 50 ◦C, 10 min at 95 ◦C, 40 thermal cycling of 15 s denaturation, and 10 min of annealing / and extension at 60 ◦C. 2.2.5. Calculation of relative quantification (RQ) (relative expression): By employing passive reference dye (ROX) to normalize the fluorescence and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a reference gene, the conventional double delta threshold cycle (ΔΔ Ct) method for relative quantification (RQ) was employed to calculate the expression of the examined genes. The Ct values of the reference gene and the examined genes were computed using Applied Biosystems Step One plus software. The analysis of the PCR data included the Ct values of the reference gene (GAPDH), the housekeeping gene, and the target genes. The negative control sample had no template cDNA. All figures were expressed as fold changes in the background levels of the control samples after being normalized to GAPDH. RQ was calculated according to the following equation: Δ Ct = Ct assessed gene of test sample – Ct reference gene Δ Ct = Ct assessed gene of control sample – Ct reference gene ΔΔ Ct = Δ Ct of test sample– Ct of the control sample RQ = 2 – (ΔΔ Ct) 2.3. Statistical evaluation With the help of the statistical program SPSS version 22, data were coded and entered. The mean and standard deviation were used to summarize the data. Chi-square (X2) test results were used to compare gender data. Using a Chi-square test, deviation from Hardy-Weinberg equilibrium (HWE) was evaluated. When comparing more than two groups, analysis of variance (ANOVA) was used, along with multiple comparisons post hoc tests. The Pearson correlation coefficient was used to determine correlations between quantitative variables. A p-value less than 0.05 was regarded as significant. 3. Result The present study was conducted on sixty women of matched age with (p-value> 0.05) (figure 1A). Participants were further split into three groups; group I: twenty healthy females as control subjects, group (II): twenty females with polycystic ovary syndrome and, group (III): twenty PCOS females treated with metformin at a dose (500 mg three times per day for 3 months). 3.1. Demographic and biochemical data characteristics (figure 1&table2) PCOS patients’ group and those treated with metformin showed statistically increased BMI, LH, Testosterone, LDL, and TG. While they showed statistically decreased HDL level matched to the normal control group. Also, the PCOS patients group revealed a statistically increased in FBS, HbA1c, fasting insulin, HOMA-IR, TC, and TG when compared to the normal control and those treated with metformin. (p-value <0.05). Significant increase in BMI in both PCOS and those treated with metformin compared to normal control subjects (p1 <0.001) (p2 =0.003), while no significant difference in BMI between PCOS patients and those treated with metformin (p3=0.3) (figure1B). Significant higher FBS levels in PCOS patients matched both the control group and those treated with metformin. (p1=0.007) (p3=0.015), While no significant difference in FBS between PCOS after treatment with metformin and the control group. (p2=0.9) (figure 1C). Significant higher level of HbA1c among PCOS patients compared to both the control group and those treated with metformin. (p1<0.001) (p3 <0.001), while no significant difference in HbA1c between PCOS after metformin treatment and the control group. (p2=0.6) (figure 1D). Fasting insulin levels in PCOS patients showed significantly higher compared to both the control group and those treated with metformin. (p1<0.001) (p3<0.001), while no significant difference in Fasting insulin between PCOS after metformin treatment and the control group. (p2=0.3) (figure 1E). LH levels in both PCOS patients and those treated with metformin showed a significant increase compared to the control group. (p1<0.001) (p20.05) (figure 1F&G), while the testosterone level in both PCOS patients and those treated with metformin showed a significantly increased compared to the control group. (p1<0.001) (p2<0.001) with no significant difference in testosterone between PCOS patients and those treated with metformin. (p3=0.7) (figure 1H). Significant high levels of LDL in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2 =0.006) with no significant difference in LDL between PCOS patients and those treated with metformin. (p3=0.07) (figure 1I). Significantly decreased HDL levels in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2=0.04), while no significant difference in HDL between PCOS patients and those treated with metformin. (p3=0.07) (Figure 1J). significant low TC level in a treated patient with metformin compared to the PCOS group. (p3=0.003), while no significant difference in TC between PCOS patients and those treated with metformin compared to the control group (p1=0.2) (p2=0.3) (figure 1K). Significant increase in TG levels in both PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2=0.03), while there was a significant decrease in TG level after metformin treatment compared to PCOS patients (p3=0.001) (figure 1L). Significant increase in HOMA in PCOS patients compared to the control group and those treated with metformin. (p1<0.001) (p3<0.001), while no significant difference in HOMA between PCOS after metformin treatment and the control group. (p2=0.6) (figure 1M). 3.2. Expression levels of PI3K, AKT, ERK, Glut 4, miR-486-5p, and miR-483-5p genes. Significant decrease in miRNA 486 level in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2<0.001) But significantly increased after metformin treatment compared to PCOS patients. (p3 <0.001), a significant decrease in miRNA 483 levels in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2<0.001) While it was significantly increased after metformin treatment compared to PCOS patients. (p3 <0.001), a significant increase in AKT levels in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2<0.001) While it was significantly decreased after metformin treatment compared to PCOS patients. (p3 <0.001), a significant increase in PI3K levels in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2<0.001) While it was significantly decreased after metformin treatment compared to PCOS patients. (p3 <0.001), a significant decrease in ERK levels in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2<0.001), a significant decrease in GLUT4 levels in PCOS patients and those treated with metformin compared to the control group. (p1<0.001) (p2<0.001) While it was significantly increased after metformin treatment compared to PCOS patients. (p3 <0.001). (Table 3, figure 2). 3.3. Correlation between miRNS 486 &PI3K and AKT among the studied groups: Significant inverted correlation between miRNA 486 and PI3K in the studied groups and a significant inverted correlation between miRNA 486 and AKT in the studied groups. (Table 4 figure 3). 3.4. Correlation between miRNA 483&GLUT4 among the studied groups: significant direct correlation between miRNA 483 and GLUT4 among the studied groups (table 5). 4. Discussion Hyperandrogenism and ovarian abnormalities are two features of polycystic ovary syndrome (PCOS), which is caused by a malfunction in the hypothalamic-pituitary-ovarian axis ( 11 ). Clinically, insulin resistance and hyperandrogenism are the primary causes of reproductive and metabolic problems in women with PCOS ( 12 ). In the present study, we compared 3 groups (group 1 as a control; group 2 as PCOS patients, and group 3 as PCOS patients after metformin treatment for 3 months). Studied parameters included: PI3K/AKT pathway target genes; GLUT 4 and miR486, and miR483. In our study, PCOS women's BMI and LH levels significantly increased when compared to the healthy control subjects (p 0.001). Our findings were in line with those of ( 13 ) who discovered that PCOS patients' BMI significantly increased when compared to the control group. In contrast, they showed that there were no appreciable variations in LH levels between the research groups. When compared to the normal control group and those receiving metformin treatment, the PCOS patient group in the current study demonstrated statistically significant increases in FBS, HbA1c, fasting insulin, HOMA-IR TC, TG, LDL, and testosterone while there was a significant decrease in HDL levels (p-value 0.05). In the same vein, ( 14 ) discovered that individuals with PCOS had significantly higher levels of (BMI), (T), (FBG), and (INS) of fasting insulin than did healthy controls (p0.05). Like how ( 15 ) confirmed our findings, they discovered that the PCOS group had considerably lower levels of HDL, FSH, and E2 than the controls while significantly higher levels of BMI, fasting insulin, HOMA-IR, LDL, TG, TC, testosterone, and LH were present. Furthermore, ( 16 ) confirmed our findings by finding that there was a statistically significant difference in BMI, FBS, HbA1c, fasting insulin, HOMA-IR TC, TG, and LDL in PCOS women compared to the control group in his study of 67 women, comprising 32 with PCOS and 35 age-matched controls. (0.05 p-value) On the other hand, ( 13 ) found that there was no significant difference between the study groups in terms of mean fasting blood sugar (FBS), FSH, and fasting insulin levels (40 women with PCOS and 36 healthy women). By preventing gluconeogenesis and adipogenesis, metformin can lower the amount of glucose produced by the liver and increase the insulin sensitivity of peripheral tissues. Reduce obesity and metabolic diseases as well. Numerous studies have demonstrated that metformin can help women with PCOS conceive by regulating menstrual cycles, restoring ovulation, and even correcting menstrual patterns ( 17 ). After treating PCOS women with metformin (500 mg three times daily for three months), there was an improvement in some biochemical markers as demonstrated by the significantly lower levels of fasting insulin, HOMA-IR, TC, TG, and FBS in the current study. (p-value 0.05), but no variations in testosterone, HDL, LDL, LH, or BMI were found to be statistically significant. These results are consistent with those of ( 18 ), who examined the impact of metformin therapy on PCOS patients over 12 weeks and discovered that parameters related to lipid metabolism (LDL and HDL) were similar in PCOS patients before and after metformin therapy, while glucose and insulin levels tended to drop. Although there are no statistically significant variations in FBS and fasting insulin, the HOMA-IR value is significantly lower after treatment with a drop of 0.5 points (p 0.05). Additionally, there was a significant drop in both TG and TC (p 0.05). On the other hand, ( 19 ) found that overweight women with the polycystic ovarian syndrome who used metformin saw significant improvements in their endocrine and metabolic indicators, such as testosterone, FSH, LH, and LDL. The secretory indices of fasting insulin, HOMA-IR, HDL, TC, TG, and FBS were not affected by metformin, though. As miRNA 483-5p and miRNA 486-5p target mediators of insulin-like growth factor (IGF) signaling, including IGF-I receptor (IGF1R) and PI3K regulatory subunit 1 (alpha) (PIK3R1), and are observed to be reduced in plasma of diabetic patients, several miRNAs play an important role in the pathogenesis of PCOS. ( 20 ). These miRNAs are involved in the death of human primary T-helper cells through apoptosis. Apoptotic cell death has also been linked to PCOS, which may explain PCOS' subfertility and abnormal follicular development ( 21 ). However, roughly 27% of miR-486's verified target genes are associated with insulin sensitivity in PCOS ( 22 ). MiRNA483 and miRNA486 were shown to be significantly downregulated in PCOS patients compared to the control group in the current study but significantly upregulated after metformin treatment. (p1 < 0.001). Whereas gene expressions of PI3K/AKT downstream signalling pathway molecules were significantly upregulated in PCOS patients compared to the control group, with significant downregulation after metformin treatment (p < 0.001). These findings suggest a role of miRNA486 and miRNA483 in the regulation of these genes and affect the insulin signalling mechanism and PCOS pathogenesis. Finally, we found that GLUT 4 gene expression was downregulated in the PCOS group compared to the control group (p < 0.001) with significant upregulation after metformin treatment. These findings support the findings of ( 23 ) that the expression of miRNA-486-5p was much lower in PCOS tissues than in normal tissues, suggesting that miRNA 486-5p may prevent the proliferation of ovarian granulosa cells, hence preventing the onset of PCOS. Additionally, ( 24 ) demonstrated that the expression of miRNA 486-5p in PCOS serum was considerably lower than that of the control group (p 0.05) and related to the pathways of reproductive disorders but not with anti mullerian hormone (AMH) or metabolic parameters. Oppositely A prior investigation by ( 25 ) using a rat model of polycystic ovarian syndrome revealed that the PCOS model had considerably greater levels of miR-486 expression. Additionally, our findings supported the findings of ( 26 ) that PCOS patients' cumulus cells dramatically downregulate the expression of miR-483-5p and miR-486-5p (p 0.001). In PCOS cumulus cells, IGF2 (the miR483 host gene) expression was dramatically downregulated (P 0.001). These findings suggested that miR483 may be crucial in lowering insulin resistance and that downregulated miR-486-5p may boost cumulus cell proliferation through the activation of PI3K/Akt. ( 27 ) shows that miR483 can control Notch3/MAPK3 expression and progesterone levels in PCOS patients' cumulus GCs and follicular fluid. MiR-483 was considerably down-regulated in the lesioned ovarian cortex of PCOS patients, according to research ( 28 ) that agreed with our findings (P 0.001). According to these findings, miR-483 is a PCOS suppressor that inhibits cell proliferation by targeting IGF1 and is involved in insulin-induced cell proliferation. As a result, miR-483 offers a potential substitute for PCOS diagnosis and treatment. Since we discovered that miRNA483 and miRNA486 expression was considerably upregulated after metformin administration, our work is the first to demonstrate a link between metformin treatment and (miRNA483 and miRNA486 expression) among PCOS. (p < 0.05). ( 29 ) demonstrated that metformin can prevent the proliferation of breast cancer cells by blocking the miR-483-3p/METTL3/m6A/p21 pathway, which was reported to be increased by metformin. Furthermore ( 30 ) suggest that metformin treatments lead to the upregulation of certain miRNAs and the downregulation of others. The authors reported that metformin has a significant effect on visceral preadipocyte differentiation, subsequently insulin resistance. Previous research has demonstrated that endometrial cancer and insulin resistance are significantly affected when the PI3K-Akt signaling pathway is activated in PCOS women ( 7 ). In this study, we discovered that PI3K and AKT were upregulated in the PCOS group in comparison to the control (p 0.001) and downregulated in the PCOS group after metformin administration in comparison to PCOS women before treatment (p 0.001). ( 31 ) who discovered that PCOS mice have considerably higher levels of pAKT/AKT expression compared to the control group (P 0.01). The expression and phosphorylation of Akt and ERK1/2 were found to be significantly higher in PCOS endometrium tissues compared to controls (p .05) in a study by ( 32 ) that investigated the relationship between activation of the Akt and ERK1/2 signaling pathways and endometrium malignant transformation in polycystic ovary syndrome. Additionally, PCOS patients with endometrial hyperplasia and cancer had significantly greater levels of p-Akt (p = .018) and p-ERK1/2 (p = .035) expression than those with normal endometrium tissues. Metformin has been shown by ( 33 ) to restore the cellular metabolic sensors AMPK, p38MAPK, and PI3K/AKT, which are responsible for insulin sensitivity and glucose absorption. Metformin is believed to increase insulin sensitivity and glucose absorption by the cells via activating AMPKs and PI3K/AKT within the cell signaling pathway. In terms of GLUT4 gene expression, we discovered that it was considerably upregulated following metformin treatment in PCOS women but dramatically downregulated in the control group (p 0.001). Older research ( 34 ) suggests a direct mechanism by which metformin could reduce insulin resistance in muscle cells by reducing Histone Deacetylase 5 (HDAC5) connection with the glucose transporter type 4 (GLUT4) gene, leading to enhanced GLUT4 expression in human primary myotubes. In the same vein, reference ( 35 ) claims that Metformin has been demonstrated to raise GLUT-4 protein and mRNA levels in soleus muscle from diabetic rats (caused by streptozotocin). The findings of ( 36 ) linked the overexpression of miR-93 with the reduced expression of GLUT4 and poor glucose transmembrane transport in PCOS patients, which confirmed our findings. Another study ( 37 ) indicated that miR-33b-5p may have played a role in the inhibition of GLUT4 synthesis, which led to PCOS IR. MiRNA486 and both PI3K and AKT showed a strong inverted association in our investigation. While across the groups under study, there was a substantial direct association between miRNA483 and GLUT4. Therefore, we can surmise that miRNA486 and miRNA483 downregulation may contribute to the etiology of PCOS, influence glucose metabolism, and result in IR in PCOS. Metformin's upregulation of those miRNAs affects glucose metabolism by controlling the expression of GLUT4, ameliorates PCOS-related insulin resistance, and improves PCOS-related hormonal imbalance by controlling the PI3K/AKT signaling pathway. It is necessary to conduct an additional study on the molecular signaling pathways of miRNA (miR-486-5p and miR-483-5p) and PCOS in humans. Future research is required to determine the impact of miRNA (miR-486-5p and miR-483-5p) overexpression on the expression of the downstream target genes for PI3K/AKT signaling, including GLTU4, ERK, AKT, and serine/threonine kinase 1. Declarations Author contributions: Heba S. Omar participated in the debate and wrote the initial manuscript, figure legends, text descriptions of the histology observations, and interpretations. Osama Ahmed performed biochemical and gene investigations, analysis, and interpretation, while Miriam Safwat took part in the manuscript's writing and data search. Maha Gomaa took part in the biochemical analysis, connected the research data, and produced the paper's final draft. Hanan Fouad and Eman Mohammed gathered information from the literature and carried out the morphometric analysis, investigation, and result correlation. The final draft of the work was approved by all authors. Data availability The data used and/or analyzed during this study are available from the corresponding author upon reasonable request. Declarations Conflict of interest: The authors have no conflicts of interest or other disclosures to report. Ethical approval : The study was designed and conducted according to ethical norms approved by the Local Ethics Committee of Cairo University, Faculty of Medicine, and written informed consent from all females (IRB number (MD-284-2020). Acknowledgments : We are grateful to the patients for their contribution to this study and the authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4331391DSR06). 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(2020). Metformin versus the combined oral contraceptive pill for hirsutism, acne, and menstrual pattern in polycystic ovary syndrome. The Cochrane database of systematic reviews, 8(8), CD005552. Pradas, I., Rovira-Llopis, S., Naudí, A., Bañuls, C., Rocha, M., Hernandez-Mijares, A., Pamplona, R., Victor, V. M., & Jové, M. (2019). Metformin induces lipid changes on sphingolipid species and oxidized lipids in polycystic ovary syndrome women. Scientific reports, 9(1), 16033. Guan, Y., Wang, D., Bu, H., Zhao, T., & Wang, H. (2020). The Effect of Metformin on Polycystic Ovary Syndrome in Overweight Women: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. International journal of endocrinology, 2020, 5150684. Peng, Y., Dai, Y., Hitchcock, C., Yang, X., Kassis, E. S., Liu, L., Luo, Z., Sun, H. L., Cui, R., Wei, H., Kim, T., Lee, T. J., Jeon, Y. J., Nuovo, G. J., Volinia, S., He, Q., Yu, J., Nana-Sinkam, P., & Croce, C. M. (2013). 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(2016). Metformin-suppressed differentiation of human visceral preadipocytes: Involvement of microRNAs. International journal of molecular medicine, 38(4), 1135–1140. Yang, D., Wang, Y., Zheng, Y., Dai, F., Liu, S., Yuan, M., Deng, Z., Bao, A., & Cheng, Y. (2021). Silencing of lncRNA UCA1 inhibited the pathological progression in PCOS mice through the regulation of PI3K/AKT signaling pathway. Journal of ovarian research, 14(1), 48. Tian, W., Zhang, H., Zhang, Y., Wang, Y., Zhang, Y., Xue, F., Song, X., & Zhang, H. (2020). High level of visfatin and the activation of Akt and ERK1/2 signaling pathways are associated with endometrium malignant transformation in polycystic ovary syndrome. Gynecological endocrinology: the official journal of the International Society of Gynecological Endocrinology, 36(2), 156–161. Naghiaee, Y., Didehdar, R., Malekpour-Dehkordi, Z., Pourrajab, F., & Mohiti-Ardakani, J. (2020). Descending Expression of miR320 in Insulin-Resistant Adipocytes Treated with Ascending Concentrations of Metformin. Biochemical genetics, 58(5), 661–676. McGee S.L., van Denderen B.J.W., Howlett K.F., Mollica J., Schertzer J.D., Kemp B.E., Hargreaves M. (2008). AMP-Activated Protein Kinase Regulates GLUT4 Transcription by Phosphorylating Histone Deacetylase 5. Diabetes.; 57:860–867. Diamanti-Kandarakis, E., Christakou, C. D., Kandaraki, E., & Economou, F. N. (2010). Metformin: an old medication of new fashion: evolving new molecular mechanisms and clinical implications in polycystic ovary syndrome. European journal of endocrinology, 162(2), 193–212. Chen YH, Heneidi S, Lee JM, Layman LC, Stepp DW, Gamboa GM, et al. (2013). miRNA-93 inhibits GLUT4 and is overexpressed in adipose tissue of polycystic ovary syndrome patients and women with insulin resistance. Diabetes.;62(7):2278–86. Yang Y, Jiang H, Xiao L, Yang X. (2018). MicroRNA-33b-5p is overexpressed and inhibits GLUT4 by targeting HMGA2 in polycystic ovarian syndrome: an in vivo and in vitro study. Oncol Rep.;39(6):3073–85. Tables Table (1): The primer sequences of the studied genes and miRNAs. Gene symbol Primer sequence from 5′- 3′ F: Forward primer, R: Reverse primer PI3K NM_006219.3 https://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?db=nucleotide&id=1698173417 Forward 5’-TTGGAATAGTAGCAGGCGGC-3’ Reverse 5’-CGCCCAGATGTCAAGGATGT-3’ ERK D31661.1 https://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?db=nucleotide&id=495677 Forward 5’-AAGAGATGGATGTGGGTTCCA-3’ Reverse. 5’-GGTCCGTAGCCAGTTGTTCT-3’ Serine/Threonine kinase 1 (AKT1), NM_001382431.1 https://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?db=nucleotide&id=1838745030 Forward 5’-CCGAAGACGGGAGCAGG-3’ Reverse 5’-ATGGAAAGCAGGCCAGACTC-3’ GLUT 4 M91463.1 https://www.ncbi.nlm.nih.gov/tools/primer-blast/primertool.cgi?ctg_time=1668587361&job_key=ZG67v2BSbfpKwP3F8KXZ94q-yMWnrdPYpg Forward 5 ’ -CCCTCAGAAGGTGATTGAACAG-3 ’ Reverse 5 ’ -AGAGATGATACCAATGAGGAAGG-3 ’ MiRNA486-5p doi: 10.1042/BSR20200392 Forward 5 ’ -GGCAGCTCAGTACAGGATAAA-3 ’ Reverse 5 ’ - CGGGGCAGCUCAGUACAGGAT - 3 ’ MiRNA483-5p doi: 10.12659/MSM.897301 F 5′-ACACTCCAGCTGGGTCCAACATTGTCTTTA G-3′ R 5′-TGGTGTCGTGGAGTCG-3′ GAPDH doi: 10.12659/MSM.897301 F 5′-GAAGGTGAAGGTCGGAGTC-3′ R 5′-GAAGATGGTGATGGGATTG-3′ Table (2): mean values ± SD of some demographic and biochemical data among the studied groups. Groups/ demographic and biochemical data Normal PCOS Metformin treated p1 value p2 value p3 value Age 24.6±4.65 23.55±4.47 23.3±3.51 0.64 0.6 0.9 BMI 25.74±2.06 30.21±3.79 29.01±2.01 <0.001 0.003 0.3 FBS (mg\dl) 85.48±9.08 97.15±17.26 86.46±7.57 0.007 0.9 0.015 HB A1c % 5.1±0.41 5.85±0.61 5.24±0.25 <0.001 0.6 <0.001 fasting insulin(mlU\l) 5.71±1.04 12.34±4.57 7.12±1.52 <0.001 0.3 <0.001 FSH (IU\L) 6.72±2.14 6.27±1.78 7.12±1.28 0.6 0.7 0.2 LH (IU\L) 4.14±1.75 10.31±4.65 10.69±3.88 <0.001 <0.001 0.9 Testosterone (ng\dl) 31.58±11.62 75.89±23.98 71.67±21.03 <0.001 <0.001 0.7 LDL (mg\dl) 115.33±11.85 149.59±25.17 136.7±20.41 <0.001 0.006 0.07 HDL (mg\dl) 61.32±9.83 50.1±8.11 55.01±5.74 <0.001 0.04 0.07 TC (mg\dl) 206.75±23.09 220.99±37.56 192.85±13.77 0.2 0.3 0.003 TG (mg\dl) 138.96±12.66 169.25±19.19 152.42±14.21 <0.001 0.03 0.001 HOMA-IR 1.2±0.19 3.09±1.68 1.53±0.4 <0.001 0.6 <0.001 Data were expressed as Mean ± SD, and p-value <0.05 was significant. P1 value: comparison between PCOS and normal control; P2value: comparison between metformin-treated and normal control; P3value: comparison between PCOS and metformin-treated Table (3): levels of PI3K, AKT, ERK, Glut 4, miR-486-5p, and miR-483-5p genes by real-time PCR among different studied groups. Groups/ Genes Normal PCOS Metformin treated p1value p2 value p3value MIR486 1.03±0.06 0.32±0.18 0.67±0.16 <0.001 <0.001 <0.001 MIR483 1.03±0.03 0.41±0.16 0.85±0.11 <0.001 <0.001 <0.001 AKT 0.28±0.14 1.02±0.03 0.6±0.14 <0.001 <0.001 <0.001 PI3K 0.41±0.2 1.02±0.02 0.63±0.14 <0.001 <0.001 <0.001 ERK 1.02±0.02 0.72±0.27 0.78±0.17 <0.001 0.002 0.5 GLUT4 1.02±0.02 0.37±0.25 0.83±0.18 <0.001 <0.001 <0.001 Data were expressed as Mean ± SD, and the pp-value<0.05 was significant. P1 value: comparison between PCOS and normal control; P2value: comparison between metformin-treated and normal control; P3value: comparison between PCOS and metformin-treated. Table (4): Correlation between miRNS 486 &PI3K and AKT among the studied groups: miRNS 486 r(p) Normal PCO Metformin treated PI3K -0.85(0.0001*) -0.77(0.0001*) -0.96(0.0001*) AKT -0.84(0.0001*) -0.76(0.0001*) -0.98(0.0001*) Table 5: Correlation between miRNS 483&GLUT4 among the studied groups: miRNS 483 r(p) Normal PCOS Metformin treated GLUT4 0.97(0.0001*) 0.92(0.0001*) 0.88(0.0001*) Supplementary Files Untitled.jpg Cite Share Download PDF Status: Published Journal Publication published 24 Aug, 2023 Read the published version in Molecular Biology Reports → Version 1 posted Editorial decision: Major Revisions Needed 24 Apr, 2023 Reviewers agreed at journal 11 Apr, 2023 Reviewers invited by journal 11 Apr, 2023 Editor assigned by journal 04 Apr, 2023 First submitted to journal 04 Apr, 2023 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. 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22:54:32","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":93510,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge, BMI, fasting blood sugar, HbA1c mean levels, fasting insulin, FSH, LH, testosterone, LDL, HDL, TC, TG, and HOMA mean levels among different studied groups.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData were expressed as Mean ± SDp-valuables \u0026lt;0.05 was significant.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(*\u003cem\u003e) Denotes significant difference between PCOS patients versus control subjects.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(#) Denotes a significant difference between metformin-treated patients versus PCOS patients.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2756899/v1/7374bb57db04d2d788c7ee0f.jpg"},{"id":35736869,"identity":"6f90592e-f0b3-4f4f-bf2b-a0bb16de93d2","added_by":"auto","created_at":"2023-04-13 22:54:32","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90129,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003elevels of PI3K, AKT, ERK, Glut 4, miR-486-5p, and miR-483-5p genes by real-time PCR among different studied groups.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData were expressed as Mean ± SD, and p value \u0026lt;0.05 was significant.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(*\u003cem\u003e) Denotes significant difference between PCOS patients versus control subjects\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(#) Denotes a significant difference between metformin-treated patients versus PCOS patients.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2756899/v1/e4c67370c384dd2b2f029070.jpg"},{"id":35737905,"identity":"1a0ebdc2-6193-4c86-973c-174639ccd265","added_by":"auto","created_at":"2023-04-13 23:02:32","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":37445,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eshows a significant inverted correlation between PI3K and AKT miRNA 486 in the studied groups.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2756899/v1/dd56573512e9d66062fb325c.jpg"},{"id":35738019,"identity":"23e19170-1d6a-4ea8-91e4-5953fe078650","added_by":"auto","created_at":"2023-04-13 23:10:32","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":24895,"visible":true,"origin":"","legend":"\u003cp\u003eshows a significant direct correlation between miRNA 483 and GLUT4 among the studied groups.\u003c/p\u003e","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2756899/v1/c251f09a2c6209477ed48fe3.jpg"},{"id":42781101,"identity":"e3f7b8db-456c-422a-8c04-f9fd46a71b62","added_by":"auto","created_at":"2023-09-07 15:08:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1532383,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2756899/v1/791718e6-10e9-4d00-80f4-26edd82c7817.pdf"},{"id":35736872,"identity":"ad274b6d-6b77-4284-9617-46fe937a48ac","added_by":"auto","created_at":"2023-04-13 22:54:32","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":184181,"visible":true,"origin":"","legend":"","description":"","filename":"Untitled.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2756899/v1/1e0334fe77a7469c73fadd50.jpg"}],"financialInterests":"","formattedTitle":"Do noncoding RNAs genes modulate PI3K/AKT signaling pathway in Polycystic ovary syndrome","fulltext":[{"header":"Highlights ","content":"\u003cp\u003e- PCOS is associated with multiple endocrine disorders and the most common cause is increased androgen level. \u003c/p\u003e\n\u003cp\u003e-Many differentially expressed miRNAs(miR-486-5p and miR-483-5p) \u0026nbsp;in PCOS women are involved in pathological insulin signaling processes, the disorder secretion of inflammatory factors, and hormones.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e-The most relevant genes involved in steroidogenesis, (miR-486-5p and miR-483-5p) and their controversial properties. PCOS is a complex genetic syndrome. the expression of the genes for PI3K/AKT signaling, including GLTU4, ERK, AKT, and serine/threonine kinase 1 plays a key role in the pathogenesis of PCOS.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003ePolycystic ovary syndrome (PCOS) is a multifactorial endocrine disorder. It is known to be associated with excess androgen, ovarian dysfunction, endocrine disruption, insulin resistance (IR), infertility, obesity, and metabolic disorders of glucose (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). PCOS is considered the most endocrinal illness in females of reproductive age (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). It affects approximately 4\u0026ndash;18% of all females of childbearing age all over the world (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the presence of compensatory hyperinsulinemia, insulin resistance (IR) is associated with a reduction in liver sex hormone binding globulin (SHBG) production and an increase in ovarian/adrenal production of androgens. Elevated levels of insulin increase the secretion of GnRH, with subsequent disturbance of the action of LH and FSH, development of hyperandrogenism, and ovulatory dysfunction (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The important reason for hyperandrogenism in females with PCOS is an upregulated expression of rate-limiting enzymes of steroidogenesis (cytochrome p450c17) 3β-hydroxysteroid dehydrogenase(3β-HSD) and 17β-hydroxysteroid dehydrogenase (17βHSD) enzymes in the theca cells of the ovaries (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Phosphoinositide 3-kinase (PI3K) protein family can be split into 3 types (I, II, and III) according to their substrate preference and structure. Class I is the most important one as it has an important effect on many pathological and physiological conditions. At the plasma membrane, PI3K is activated near its substrate. In addition to fibroblast growth factor, vascular endothelial growth factor (VEGF), and insulin, PI3K can be activated by several growth factors (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePI3K-Akt signaling pathway stimulation by insulin; activation of insulin receptors, lead to increase insulin receptor substrates (IRS), which bind with PI3K which produces phosphoinositide triphosphate (PIP3). The PIP3 acts on phosphoinositide-dependent kinase 1 (PDK1), leading to the phosphorylation of the Akt protein. Activated Akt protein affects downstream molecules such as GLUT4; it influences glucose metabolism (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003emiRNAs are the Master Maestro of the human genome. They play a pivotal role in the post-transcriptional modifications in many interacting signaling pathways in different oncological and non-oncological pathological states. miR486-5p and miR486-3p act as prognostic and diagnostic markers in many diseases such as insulin resistance, hypertension, osteoarthritis, and metabolic syndromes (MS). In Egyptian males, miR486-5p was found to be a prognostic factor for insulin resistance (IR), elevated blood pressure (BP), and PCOS (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, several pieces of evidence suggested the involvement of miR483 over-expression in some pathological non-oncologic conditions like cardiovascular diseases, DM, obesity, non-alcoholic fatty liver disease (NAFLD), systemic sclerosis, rheumatoid arthritis, and metabolic syndrome (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study aims to determine whether metformin affects gene expression of PI3K, AKT, ERK, GLUT4, miR486-5p, and miR483-5p as well as to assess the status of insulin resistance and hormonal imbalance associated with PCOS patients.\u003c/p\u003e"},{"header":"2. Method","content":"\u003cp\u003eThe study was conducted under the Declaration of Helsinki and approved by the Local Ethics Committee of Cairo University, Faculty of Medicine, and written informed consent from all females (IRB number(284). \u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this case-control study, 60 females aged 25 to 35 were studied at Cairo University\u0026apos;s Faculty of Medicine, Unit of Biochemistry and Molecular Biology. During the period January 2022 to June 2022, participants were recruited from the Obstetrics and Gynecology department at Minia University, Egypt.\u003c/p\u003e\n\u003cp\u003ePCOS patients diagnosed according to the revised 2003 consensus on diagnostic criteria and long-term health risks associated with PCOS were eligible (\u003cstrong\u003e10\u003c/strong\u003e). There are three criteria for diagnosing PCOS: Oligo ovulation indoor an-ovulation, clinical indoor biochemical evidence of hyperandrogenism, and polycystic ovarian morphology. The case must meet at least two of the three criteria to be classified as PCOS.\u003c/p\u003e\n\u003cp\u003eSubjects of the study were subdivided into three groups: Group Ⅰ: \u0026nbsp;included 20 age-matched females as a control group. \u0026nbsp;Group Ⅱ: included 20 females of reproductive age with polycystic ovary syndrome without complication, and who did not receive any hormone drugs or oral contraceptives. Group Ⅲ: included 20 of the PCOS group who were treated with metformin at a dose (500 mg three times per day for 3 months). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; Exclusion criteria included: females in the postmenopausal phase and patients with any condition that causes hyperandrogenism, or hypothyroidism. Female patients with liver, kidney, and heart diseases were also excluded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; The history of all eligible females was taken in detail, including age at the time of examination, disease duration, and types of drugs taken. In addition to measuring weight, height, and body mass index, a thorough clinical examination focused on endocrine gland disease. By local standards, routine laboratory investigations were conducted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003e2.1. Sample collection:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter signing written informed consent: Five mL venous blood samples were taken from all subjects using the BD Vacutainer system during the 3rd, 4\u003csup\u003eth\u003c/sup\u003e, and 5th days of the menstrual cycle and at any time for those who had amenorrhea, (NB: two samples were collected from Group Ⅲ before and after metformin administration) kept at -80\u0026nbsp;\u0026deg;C until the time of analysis of the following parameters:\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eGene expression of PI3K/AKT\u0026nbsp;downstream signaling target genes: extracellular signal-regulated kinase (ERK), serine/threonine kinase 1 (AKT), and GLUT4 in the peripheral blood by real-time PCR.\u003c/li\u003e\n \u003cli\u003eEvaluation of miR486-5p and miR483-5p in peripheral blood by real-time PCR.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003e2.2. Molecular Biology Techniques:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of expression levels of PI3K, AKT, ERK, GLUT 4,\u003c/strong\u003e \u003cstrong\u003emiR486-5p, and miR483-5p in the whole blood by real-time\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eqRT PCR\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.2.1.RNA extraction:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eRNA was isolated using\u0026nbsp;miRNAs mini kit (Qiagen, Germany, Cat. No. 217004) permitting the manufacturer\u0026rsquo;s recommendations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.2.2. Quantitation of isolated RNAs:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe absorbance of isolated miRNA was measured by Nanodrop\u0026reg; spectrophotometer at 260 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.2.3. Amplification and quantification of the genes using Reverse Transcription - Polymerase Chain Reaction (RT-PCR):\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Transcript\u003c/em\u003e\u003csup\u003e\u0026reg;\u003c/sup\u003e Green One-Step qRT-PCR Super Mix kit (Transgenbiotech, China, Cat No. AQ211) was used permitting the manufacturer\u0026rsquo;s recommendations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.2.4. Primer selection:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtained the primers for PCR from GenBank RNA sequences cited at http://www.ncbi.nlm.nih.gov/tools/primer-blast. When selecting the ideal primer pair, the following factors were considered: melting temperature (Tm: 60\u0026ndash;650C), guanine, cytosine content (40%\u0026ndash;60%), and amplicon length between 90 and 200 bp.\u003c/p\u003e\n\u003cp\u003eSoftware version 3.1 of the StepOnePlus Real-Time PCR system (Applied Biosystems, USA) was used to examine gene expression. SYBR\u0026reg; Green (ThermoFisher, USA) was used to measure relative gene expression.\u003c/p\u003e\n\u003cp\u003eA hardening temperature of 60◦C was adjusted for all primer sets. Real-time PCR \u0026nbsp;was done in 25\u0026mu;L final volume containing SYBR Green master mix, 900 nmol/L of every PCR primer, and 3 \u0026mu;L of cDNA. Amplification conditions were done based on the manufacturer references: 2 min at 50 ◦C, 10 min at 95 ◦C, 40 thermal cycling of 15\u003csup\u003es\u003c/sup\u003e denaturation, and 10 min of annealing / and extension at 60 ◦C.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.2.5. Calculation of relative quantification (RQ) (relative expression):\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBy employing passive reference dye (ROX) to normalize the fluorescence and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a reference gene, the conventional double delta threshold cycle (\u0026Delta;\u0026Delta; Ct) method for relative quantification (RQ) was employed to calculate the expression of the examined genes. The Ct values of the reference gene and the examined genes were computed using Applied Biosystems Step One plus software. The analysis of the PCR data included the Ct values of the reference gene (GAPDH), the housekeeping gene, and the target genes. The negative control sample had no template cDNA. All figures were expressed as fold changes in the background levels of the control samples after being normalized to GAPDH.\u003c/p\u003e\n\u003cp\u003eRQ was calculated according to the following equation:\u003c/p\u003e\n\u003cp\u003e\u0026Delta; Ct = Ct assessed gene of test sample \u0026ndash; Ct reference gene\u003c/p\u003e\n\u003cp\u003e\u0026Delta; Ct = Ct assessed gene of control sample \u0026ndash; Ct reference gene\u003c/p\u003e\n\u003cp\u003e\u0026Delta;\u0026Delta; Ct = \u0026Delta; Ct of test sample\u0026ndash; Ct of the control sample \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRQ = 2 \u0026ndash; (\u0026Delta;\u0026Delta; Ct)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003e2.3. Statistical evaluation\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWith the help of the statistical program SPSS version 22, data were coded and entered. The mean and standard deviation were used to summarize the data. Chi-square (X2) test results were used to compare gender data. Using a Chi-square test, deviation from Hardy-Weinberg equilibrium (HWE) was evaluated. When comparing more than two groups, analysis of variance (ANOVA) was used, along with multiple comparisons post hoc tests. The Pearson correlation coefficient was used to determine correlations between quantitative variables. A p-value less than 0.05 was regarded as significant.\u003c/p\u003e"},{"header":"3. Result ","content":"\u003cp\u003eThe present study was conducted on sixty women of matched age with (p-value\u0026gt; 0.05) (figure 1A). Participants were further split into three groups; group I: twenty healthy females as control subjects, group (II): twenty females with polycystic ovary syndrome and, group (III): twenty PCOS females treated with metformin at a dose (500 mg three times per day for 3 months).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003e3.1. Demographic and biochemical data characteristics (figure 1\u0026amp;table2)\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePCOS patients\u0026rsquo; group and those treated with metformin showed statistically increased BMI, LH, Testosterone, LDL, and TG. While they showed statistically decreased HDL level matched to the normal control group.\u003c/p\u003e\n\u003cp\u003eAlso, the PCOS patients group revealed a statistically increased in FBS, HbA1c, fasting insulin, HOMA-IR, TC, and TG when compared to the normal control and those treated with metformin. (p-value \u0026lt;0.05).\u0026nbsp;Significant increase in BMI in both PCOS and those treated with metformin compared to normal control subjects (p1 \u0026lt;0.001) (p2 =0.003), while no significant difference in BMI between PCOS patients and those treated with metformin (p3=0.3) (figure1B).\u003c/p\u003e\n\u003cp\u003eSignificant higher FBS levels in PCOS patients matched both the control group and those treated with metformin. (p1=0.007) (p3=0.015), While no significant difference in FBS between PCOS after treatment with metformin and the control group. (p2=0.9) (figure 1C). Significant higher level of HbA1c among PCOS patients compared to\u0026nbsp;both the control group and those treated with metformin. (p1\u0026lt;0.001) (p3 \u0026lt;0.001), while\u0026nbsp;no significant difference in HbA1c between PCOS after metformin treatment\u0026nbsp;and the\u0026nbsp;control group. (p2=0.6) (figure 1D).\u003c/p\u003e\n\u003cp\u003eFasting insulin levels in PCOS patients showed significantly higher compared to both the control group and those treated with metformin. (p1\u0026lt;0.001) (p3\u0026lt;0.001), while no significant difference in\u0026nbsp;Fasting insulin\u0026nbsp;between PCOS after metformin treatment and the\u0026nbsp;control group. (p2=0.3) (figure 1E).\u0026nbsp;LH levels in both PCOS patients and those treated with metformin showed a significant increase compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001) with no significant difference in LH between PCOS patients and those treated with metformin. (p3=0.9) and\u0026nbsp;no significant differences among the three groups as regards FSH levels. (p values \u0026gt;0.05)\u0026nbsp;(figure 1F\u0026amp;G), while the\u0026nbsp;testosterone level in both PCOS patients and those treated with metformin showed a significantly increased compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001) with\u0026nbsp;no significant difference in testosterone between PCOS\u0026nbsp;patients\u0026nbsp;and those treated with metformin. (p3=0.7) (figure 1H).\u0026nbsp;Significant high levels of LDL in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2 =0.006) with\u0026nbsp;no significant difference in LDL between PCOS\u0026nbsp;patients\u0026nbsp;and those treated with metformin. (p3=0.07) (figure 1I).\u0026nbsp;Significantly decreased HDL levels in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2=0.04),\u0026nbsp;while no significant difference in HDL between PCOS\u0026nbsp;patients\u0026nbsp;and those treated with metformin. (p3=0.07) (Figure 1J).\u0026nbsp;significant low TC level in a treated patient with metformin compared to the PCOS group. (p3=0.003), while\u0026nbsp;no significant difference in TC between PCOS\u0026nbsp;patients\u0026nbsp;and those treated with metformin compared to the control group\u0026nbsp;(p1=0.2) (p2=0.3) (figure 1K).\u0026nbsp;Significant increase in TG levels in both PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2=0.03), while there was a significant decrease in TG level after metformin treatment compared to PCOS patients (p3=0.001) (figure 1L).\u003c/p\u003e\n\u003cp\u003eSignificant increase in HOMA in PCOS patients compared to the control group and those treated with metformin. (p1\u0026lt;0.001) (p3\u0026lt;0.001), while no significant difference in HOMA between PCOS after metformin treatment\u0026nbsp;and the\u0026nbsp;control group. (p2=0.6) (figure 1M).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003e3.2. Expression levels of PI3K, AKT, ERK, Glut 4, miR-486-5p, and miR-483-5p genes.\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificant decrease in miRNA 486 level in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001) But significantly increased after metformin treatment compared to PCOS patients. (p3 \u0026lt;0.001), a significant decrease in miRNA 483 levels in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001) While it was significantly increased after metformin treatment compared to PCOS patients. (p3 \u0026lt;0.001), a significant increase in AKT levels in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001) While it was significantly decreased after metformin treatment compared to PCOS patients. (p3 \u0026lt;0.001), a significant increase in PI3K levels in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001) While it was significantly decreased after metformin treatment compared to PCOS patients. (p3 \u0026lt;0.001), a significant decrease in ERK levels in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001), a \u0026nbsp;significant decrease in GLUT4 levels in PCOS patients and those treated with metformin compared to the control group. (p1\u0026lt;0.001) (p2\u0026lt;0.001) While it was significantly increased after metformin treatment compared to PCOS patients. (p3 \u0026lt;0.001). (Table 3, figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003e3.3. Correlation between miRNS 486 \u0026amp;PI3K and AKT among the studied groups:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificant inverted correlation between miRNA 486 and PI3K in the studied groups and a significant inverted correlation between miRNA 486 and AKT in the studied groups. \u0026nbsp;(Table 4 figure 3). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003e3.4. Correlation between miRNA 483\u0026amp;GLUT4 among the studied groups:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003esignificant direct correlation between miRNA 483 and GLUT4 among the studied groups (table 5).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eHyperandrogenism and ovarian abnormalities are two features of polycystic ovary syndrome (PCOS), which is caused by a malfunction in the hypothalamic-pituitary-ovarian axis (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Clinically, insulin resistance and hyperandrogenism are the primary causes of reproductive and metabolic problems in women with PCOS (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, we compared 3 groups (group 1 as a control; group 2 as PCOS patients, and group 3 as PCOS patients after metformin treatment for 3 months). Studied parameters included: PI3K/AKT pathway target genes; GLUT 4 and miR486, and miR483.\u003c/p\u003e \u003cp\u003eIn our study, PCOS women's BMI and LH levels significantly increased when compared to the healthy control subjects (p 0.001). Our findings were in line with those of (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) who discovered that PCOS patients' BMI significantly increased when compared to the control group. In contrast, they showed that there were no appreciable variations in LH levels between the research groups.\u003c/p\u003e \u003cp\u003eWhen compared to the normal control group and those receiving metformin treatment, the PCOS patient group in the current study demonstrated statistically significant increases in FBS, HbA1c, fasting insulin, HOMA-IR TC, TG, LDL, and testosterone while there was a significant decrease in HDL levels (p-value 0.05). In the same vein, (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) discovered that individuals with PCOS had significantly higher levels of (BMI), (T), (FBG), and (INS) of fasting insulin than did healthy controls (p0.05). Like how (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) confirmed our findings, they discovered that the PCOS group had considerably lower levels of HDL, FSH, and E2 than the controls while significantly higher levels of BMI, fasting insulin, HOMA-IR, LDL, TG, TC, testosterone, and LH were present.\u003c/p\u003e \u003cp\u003eFurthermore, (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) confirmed our findings by finding that there was a statistically significant difference in BMI, FBS, HbA1c, fasting insulin, HOMA-IR TC, TG, and LDL in PCOS women compared to the control group in his study of 67 women, comprising 32 with PCOS and 35 age-matched controls. (0.05 p-value)\u003c/p\u003e \u003cp\u003eOn the other hand, (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) found that there was no significant difference between the study groups in terms of mean fasting blood sugar (FBS), FSH, and fasting insulin levels (40 women with PCOS and 36 healthy women).\u003c/p\u003e \u003cp\u003eBy preventing gluconeogenesis and adipogenesis, metformin can lower the amount of glucose produced by the liver and increase the insulin sensitivity of peripheral tissues. Reduce obesity and metabolic diseases as well. Numerous studies have demonstrated that metformin can help women with PCOS conceive by regulating menstrual cycles, restoring ovulation, and even correcting menstrual patterns (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter treating PCOS women with metformin (500 mg three times daily for three months), there was an improvement in some biochemical markers as demonstrated by the significantly lower levels of fasting insulin, HOMA-IR, TC, TG, and FBS in the current study. (p-value 0.05), but no variations in testosterone, HDL, LDL, LH, or BMI were found to be statistically significant.\u003c/p\u003e \u003cp\u003eThese results are consistent with those of (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), who examined the impact of metformin therapy on PCOS patients over 12 weeks and discovered that parameters related to lipid metabolism (LDL and HDL) were similar in PCOS patients before and after metformin therapy, while glucose and insulin levels tended to drop. Although there are no statistically significant variations in FBS and fasting insulin, the HOMA-IR value is significantly lower after treatment with a drop of 0.5 points (p 0.05). Additionally, there was a significant drop in both TG and TC (p 0.05).\u003c/p\u003e \u003cp\u003eOn the other hand, (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) found that overweight women with the polycystic ovarian syndrome who used metformin saw significant improvements in their endocrine and metabolic indicators, such as testosterone, FSH, LH, and LDL. The secretory indices of fasting insulin, HOMA-IR, HDL, TC, TG, and FBS were not affected by metformin, though.\u003c/p\u003e \u003cp\u003eAs miRNA 483-5p and miRNA 486-5p target mediators of insulin-like growth factor (IGF) signaling, including IGF-I receptor (IGF1R) and PI3K regulatory subunit 1 (alpha) (PIK3R1), and are observed to be reduced in plasma of diabetic patients, several miRNAs play an important role in the pathogenesis of PCOS. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese miRNAs are involved in the death of human primary T-helper cells through apoptosis. Apoptotic cell death has also been linked to PCOS, which may explain PCOS' subfertility and abnormal follicular development (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). However, roughly 27% of miR-486's verified target genes are associated with insulin sensitivity in PCOS (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMiRNA483 and miRNA486 were shown to be significantly downregulated in PCOS patients compared to the control group in the current study but significantly upregulated after metformin treatment. (p1\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Whereas gene expressions of PI3K/AKT downstream signalling pathway molecules were significantly upregulated in PCOS patients compared to the control group, with significant downregulation after metformin treatment (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings suggest a role of miRNA486 and miRNA483 in the regulation of these genes and affect the insulin signalling mechanism and PCOS pathogenesis.\u003c/p\u003e \u003cp\u003eFinally, we found that GLUT 4 gene expression was downregulated in the PCOS group compared to the control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with significant upregulation after metformin treatment.\u003c/p\u003e \u003cp\u003eThese findings support the findings of (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) that the expression of miRNA-486-5p was much lower in PCOS tissues than in normal tissues, suggesting that miRNA 486-5p may prevent the proliferation of ovarian granulosa cells, hence preventing the onset of PCOS. Additionally, (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) demonstrated that the expression of miRNA 486-5p in PCOS serum was considerably lower than that of the control group (p 0.05) and related to the pathways of reproductive disorders but not with anti mullerian hormone (AMH) or metabolic parameters.\u003c/p\u003e \u003cp\u003eOppositely A prior investigation by (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) using a rat model of polycystic ovarian syndrome revealed that the PCOS model had considerably greater levels of miR-486 expression.\u003c/p\u003e \u003cp\u003eAdditionally, our findings supported the findings of (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) that PCOS patients' cumulus cells dramatically downregulate the expression of miR-483-5p and miR-486-5p (p 0.001). In PCOS cumulus cells, IGF2 (the miR483 host gene) expression was dramatically downregulated (P 0.001). These findings suggested that miR483 may be crucial in lowering insulin resistance and that downregulated miR-486-5p may boost cumulus cell proliferation through the activation of PI3K/Akt. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) shows that miR483 can control Notch3/MAPK3 expression and progesterone levels in PCOS patients' cumulus GCs and follicular fluid.\u003c/p\u003e \u003cp\u003eMiR-483 was considerably down-regulated in the lesioned ovarian cortex of PCOS patients, according to research (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) that agreed with our findings (P 0.001).\u003c/p\u003e \u003cp\u003eAccording to these findings, miR-483 is a PCOS suppressor that inhibits cell proliferation by targeting IGF1 and is involved in insulin-induced cell proliferation. As a result, miR-483 offers a potential substitute for PCOS diagnosis and treatment.\u003c/p\u003e \u003cp\u003eSince we discovered that miRNA483 and miRNA486 expression was considerably upregulated after metformin administration, our work is the first to demonstrate a link between metformin treatment and (miRNA483 and miRNA486 expression) among PCOS. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) demonstrated that metformin can prevent the proliferation of breast cancer cells by blocking the miR-483-3p/METTL3/m6A/p21 pathway, which was reported to be increased by metformin.\u003c/p\u003e \u003cp\u003eFurthermore (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) suggest that metformin treatments lead to the upregulation of certain miRNAs and the downregulation of others. The authors reported that metformin has a significant effect on visceral preadipocyte differentiation, subsequently insulin resistance.\u003c/p\u003e \u003cp\u003ePrevious research has demonstrated that endometrial cancer and insulin resistance are significantly affected when the PI3K-Akt signaling pathway is activated in PCOS women (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we discovered that PI3K and AKT were upregulated in the PCOS group in comparison to the control (p 0.001) and downregulated in the PCOS group after metformin administration in comparison to PCOS women before treatment (p 0.001).\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) who discovered that PCOS mice have considerably higher levels of pAKT/AKT expression compared to the control group (P 0.01).\u003c/p\u003e \u003cp\u003eThe expression and phosphorylation of Akt and ERK1/2 were found to be significantly higher in PCOS endometrium tissues compared to controls (p .05) in a study by (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) that investigated the relationship between activation of the Akt and ERK1/2 signaling pathways and endometrium malignant transformation in polycystic ovary syndrome. Additionally, PCOS patients with endometrial hyperplasia and cancer had significantly greater levels of p-Akt (p\u0026thinsp;=\u0026thinsp;.018) and p-ERK1/2 (p\u0026thinsp;=\u0026thinsp;.035) expression than those with normal endometrium tissues.\u003c/p\u003e \u003cp\u003eMetformin has been shown by (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) to restore the cellular metabolic sensors AMPK, p38MAPK, and PI3K/AKT, which are responsible for insulin sensitivity and glucose absorption. Metformin is believed to increase insulin sensitivity and glucose absorption by the cells via activating AMPKs and PI3K/AKT within the cell signaling pathway.\u003c/p\u003e \u003cp\u003eIn terms of GLUT4 gene expression, we discovered that it was considerably upregulated following metformin treatment in PCOS women but dramatically downregulated in the control group (p 0.001).\u003c/p\u003e \u003cp\u003eOlder research (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) suggests a direct mechanism by which metformin could reduce insulin resistance in muscle cells by reducing Histone Deacetylase 5 (HDAC5) connection with the glucose transporter type 4 (GLUT4) gene, leading to enhanced GLUT4 expression in human primary myotubes.\u003c/p\u003e \u003cp\u003eIn the same vein, reference (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) claims that Metformin has been demonstrated to raise GLUT-4 protein and mRNA levels in soleus muscle from diabetic rats (caused by streptozotocin).\u003c/p\u003e \u003cp\u003eThe findings of (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) linked the overexpression of miR-93 with the reduced expression of GLUT4 and poor glucose transmembrane transport in PCOS patients, which confirmed our findings.\u003c/p\u003e \u003cp\u003eAnother study (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) indicated that miR-33b-5p may have played a role in the inhibition of GLUT4 synthesis, which led to PCOS IR. MiRNA486 and both PI3K and AKT showed a strong inverted association in our investigation. While across the groups under study, there was a substantial direct association between miRNA483 and GLUT4.\u003c/p\u003e \u003cp\u003eTherefore, we can surmise that miRNA486 and miRNA483 downregulation may contribute to the etiology of PCOS, influence glucose metabolism, and result in IR in PCOS. Metformin's upregulation of those miRNAs affects glucose metabolism by controlling the expression of GLUT4, ameliorates PCOS-related insulin resistance, and improves PCOS-related hormonal imbalance by controlling the PI3K/AKT signaling pathway.\u003c/p\u003e \u003cp\u003eIt is necessary to conduct an additional study on the molecular signaling pathways of miRNA (miR-486-5p and miR-483-5p) and PCOS in humans. Future research is required to determine the impact of miRNA (miR-486-5p and miR-483-5p) overexpression on the expression of the downstream target genes for PI3K/AKT signaling, including GLTU4, ERK, AKT, and serine/threonine kinase 1.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeba S. Omar participated in the debate and wrote the initial manuscript, figure legends, text descriptions of the histology observations, and interpretations. Osama Ahmed performed biochemical and gene investigations, analysis, and interpretation, while Miriam Safwat took part in the manuscript\u0026apos;s writing and data search. Maha Gomaa took part in the biochemical analysis, connected the research data, and produced the paper\u0026apos;s final draft. Hanan Fouad and Eman Mohammed gathered information from the literature and carried out the morphometric analysis, investigation, and result correlation. The final draft of the work was approved by all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data used and/or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations Conflict of interest:\u003c/strong\u003e The authors have no conflicts of interest or other disclosures to report.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e: The study was designed and conducted according to ethical norms approved by the Local Ethics Committee of Cairo University, Faculty of Medicine, and written informed consent from all females (IRB number (MD-284-2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgments\u003c/strong\u003e: We are grateful to the patients for their contribution to this study and the authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4331391DSR06).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003cstrong\u003eLi, Y., Chen, C., Ma, Y., Xiao, J., Luo, G., Li, Y., \u0026amp; Wu, D. 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(2018).\u003c/strong\u003e MicroRNA-33b-5p is overexpressed and inhibits GLUT4 by targeting HMGA2 in polycystic ovarian syndrome: an in vivo and in vitro study. Oncol Rep.;39(6):3073\u0026ndash;85.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable (1):\u003c/strong\u003e The primer sequences of the studied genes and miRNAs.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"738\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene symbol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimer sequence from 5\u0026prime;- 3\u0026prime;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eF: Forward primer, R: Reverse primer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePI3K \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eNM_006219.3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;https://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?db=nucleotide\u0026amp;id=1698173417\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eForward \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u0026rsquo;-TTGGAATAGTAGCAGGCGGC-3\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eReverse \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u0026rsquo;-CGCCCAGATGTCAAGGATGT-3\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003eERK \u0026nbsp; \u0026nbsp; D31661.1\u003c/strong\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;https://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?db=nucleotide\u0026amp;id=495677\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eForward \u0026nbsp; \u0026nbsp;5\u0026rsquo;-AAGAGATGGATGTGGGTTCCA-3\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eReverse. \u0026nbsp; 5\u0026rsquo;-GGTCCGTAGCCAGTTGTTCT-3\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSerine/Threonine kinase 1 (AKT1),\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eNM_001382431.1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ehttps://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?db=nucleotide\u0026amp;id=1838745030\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eForward 5\u0026rsquo;-CCGAAGACGGGAGCAGG-3\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eReverse 5\u0026rsquo;-ATGGAAAGCAGGCCAGACTC-3\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGLUT 4 \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eM91463.1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ehttps://www.ncbi.nlm.nih.gov/tools/primer-blast/primertool.cgi?ctg_time=1668587361\u0026amp;job_key=ZG67v2BSbfpKwP3F8KXZ94q-yMWnrdPYpg\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eForward \u0026nbsp; \u0026nbsp;5\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e-CCCTCAGAAGGTGATTGAACAG-3\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eReverse \u0026nbsp; \u0026nbsp;5\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e-AGAGATGATACCAATGAGGAAGG-3\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiRNA486-5p \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edoi: 10.1042/BSR20200392\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003eForward \u0026nbsp; \u0026nbsp; \u0026nbsp; 5\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e-GGCAGCTCAGTACAGGATAAA-3\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eReverse \u0026nbsp; \u0026nbsp; \u0026nbsp; 5\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCGGGGCAGCUCAGUACAGGAT\u003c/strong\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiRNA483-5p \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edoi: 10.12659/MSM.897301\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026nbsp; \u0026nbsp; 5\u0026prime;-ACACTCCAGCTGGGTCCAACATTGTCTTTA G-3\u0026prime;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5\u0026prime;-TGGTGTCGTGGAGTCG-3\u0026prime;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"39.97289972899729%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGAPDH \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edoi: 10.12659/MSM.897301\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"60.02710027100271%\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5\u0026prime;-GAAGGTGAAGGTCGGAGTC-3\u0026prime;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5\u0026prime;-GAAGATGGTGATGGGATTG-3\u0026prime;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (2):\u0026nbsp;\u003c/strong\u003emean values \u0026plusmn; SD of some demographic and biochemical data among the studied groups.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"709\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups/ demographic and biochemical data\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCOS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetformin treated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep1 value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep2 value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e24.6\u0026plusmn;4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e23.55\u0026plusmn;4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e23.3\u0026plusmn;3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e25.74\u0026plusmn;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e30.21\u0026plusmn;3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e29.01\u0026plusmn;2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFBS (mg\\dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e85.48\u0026plusmn;9.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e97.15\u0026plusmn;17.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e86.46\u0026plusmn;7.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHB\u003c/strong\u003e\u003cstrong\u003eA1c %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e5.1\u0026plusmn;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e5.85\u0026plusmn;0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e5.24\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003efasting insulin(mlU\\l)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e5.71\u0026plusmn;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e12.34\u0026plusmn;4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e7.12\u0026plusmn;1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFSH (IU\\L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e6.72\u0026plusmn;2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e6.27\u0026plusmn;1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e7.12\u0026plusmn;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLH (IU\\L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e4.14\u0026plusmn;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e10.31\u0026plusmn;4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e10.69\u0026plusmn;3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTestosterone (ng\\dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e31.58\u0026plusmn;11.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e75.89\u0026plusmn;23.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e71.67\u0026plusmn;21.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL (mg\\dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e115.33\u0026plusmn;11.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e149.59\u0026plusmn;25.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e136.7\u0026plusmn;20.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL (mg\\dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e61.32\u0026plusmn;9.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e50.1\u0026plusmn;8.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e55.01\u0026plusmn;5.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTC (mg\\dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e206.75\u0026plusmn;23.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e220.99\u0026plusmn;37.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e192.85\u0026plusmn;13.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG (mg\\dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e138.96\u0026plusmn;12.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e169.25\u0026plusmn;19.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e152.42\u0026plusmn;14.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.425952045133993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHOMA-IR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e1.2\u0026plusmn;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.540197461212976%\"\u003e\n \u003cp\u003e3.09\u0026plusmn;1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.181946403385048%\"\u003e\n \u003cp\u003e1.53\u0026plusmn;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.155148095909732%\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.001410437235544%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eData were expressed as Mean \u0026plusmn; SD,\u0026nbsp;\u003c/em\u003e\u003cem\u003eand p-value \u0026lt;0.05 was significant.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eP1 value: comparison between PCOS and normal\u0026nbsp;\u003c/em\u003e\u003cem\u003econtrol; P2value: comparison between metformin-treated and normal control; P3value: comparison between PCOS and metformin-treated\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (3): levels of PI3K, AKT, ERK, Glut 4, miR-486-5p, and miR-483-5p genes by real-time PCR among different studied groups.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups/ Genes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCOS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.53290529695024%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetformin treated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep1value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.680577849117174%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep2 value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep3value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIR486\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e1.03\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e0.32\u0026plusmn;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.53290529695024%\"\u003e\n \u003cp\u003e0.67\u0026plusmn;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.680577849117174%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIR483\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e1.03\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e0.41\u0026plusmn;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.53290529695024%\"\u003e\n \u003cp\u003e0.85\u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.680577849117174%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAKT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e0.28\u0026plusmn;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e1.02\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.53290529695024%\"\u003e\n \u003cp\u003e0.6\u0026plusmn;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.680577849117174%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePI3K\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e0.41\u0026plusmn;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e1.02\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.53290529695024%\"\u003e\n \u003cp\u003e0.63\u0026plusmn;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.680577849117174%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e\u003cstrong\u003eERK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e1.02\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e0.72\u0026plusmn;0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.53290529695024%\"\u003e\n \u003cp\u003e0.78\u0026plusmn;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.680577849117174%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGLUT4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e1.02\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.730337078651685%\"\u003e\n \u003cp\u003e0.37\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.53290529695024%\"\u003e\n \u003cp\u003e0.83\u0026plusmn;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.680577849117174%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.841091492776886%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eData were expressed as Mean \u0026plusmn; SD,\u0026nbsp;\u003c/em\u003e\u003cem\u003eand the pp-value\u0026lt;0.05 was significant.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eP1 value: comparison between PCOS and normal control; P2value: comparison between metformin-treated and normal control; P3value: comparison between PCOS and metformin-treated.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (4):\u003c/strong\u003e \u003cstrong\u003eCorrelation between miRNS 486 \u0026amp;PI3K and AKT among the studied groups:\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"19.365079365079364%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"80.63492063492063%\"\u003e\n \u003cp\u003e\u003cstrong\u003emiRNS 486\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003er(p)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"30.31496062992126%\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.85826771653543%\"\u003e\n \u003cp\u003ePCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"35.826771653543304%\"\u003e\n \u003cp\u003eMetformin treated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.365079365079364%\"\u003e\n \u003cp\u003ePI3K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.444444444444443%\"\u003e\n \u003cp\u003e-0.85(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.3015873015873%\"\u003e\n \u003cp\u003e-0.77(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.88888888888889%\"\u003e\n \u003cp\u003e-0.96(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.365079365079364%\"\u003e\n \u003cp\u003eAKT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.444444444444443%\"\u003e\n \u003cp\u003e-0.84(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.3015873015873%\"\u003e\n \u003cp\u003e-0.76(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.88888888888889%\"\u003e\n \u003cp\u003e-0.98(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Correlation between miRNS 483\u0026amp;GLUT4 among the studied groups:\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"19.334389857369256%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"80.66561014263074%\"\u003e\n \u003cp\u003e\u003cstrong\u003emiRNS 483\u003c/strong\u003er(p)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"30.31496062992126%\"\u003e\n \u003cp\u003eNormal \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.85826771653543%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCOS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"35.826771653543304%\"\u003e\n \u003cp\u003eMetformin treated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.365079365079364%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGLUT4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.444444444444443%\"\u003e\n \u003cp\u003e0.97(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.3015873015873%\"\u003e\n \u003cp\u003e0.92(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.88888888888889%\"\u003e\n \u003cp\u003e0.88(0.0001*)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"PCOS, miRNA 486, miRNA 483, PI3K/AKT, GLUT 4","lastPublishedDoi":"10.21203/rs.3.rs-2756899/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2756899/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and aims: \u003c/strong\u003eThe PI3K protein kinase B (PI3K/Akt) signaling pathway has crucial roles in insulin signaling and other endocrine disorders. It is the purpose of this study to validate the association of PCOS with PI3K/AKT pathway target genes, miR486-5p, and miR483-5p as well as to evaluate the outcome of metformin on the pathogenesis of PCOS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This case-controlled study included 3 subject groups: twenty healthy females (control group), twenty PCOS females before treatment, and twenty PCOS females treated with metformin at a dose (500 mg 3 times per day for three months). The following gene expressions were assessed by real-time PCR: PI3K, AKT, ERK, GLUT4, miR486-5p, and miR483-5p in the whole blood.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult: \u003c/strong\u003eThere was a significant decrease in miR486-5p and miR483-5p in the PCOS group with a significant negative correlation between miR486-5p and PI3K and a significant negative correlation between miR483-5p and ERK. Metformin treatment resulted in significant elevation of the studied miRNAs, significant downregulation of PI3K/AKT target genes, and significant amelioration of the gonadotrophic hormonal imbalance and insulin resistance markers: fasting blood glucose, HBA1C, fasting insulin, and GLUT4 gene expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003emiRNA486 and miRNA483 downregulation may contribute to the etiology of PCOS, influence glucose metabolism, and result in IR in PCOS. Metformin's upregulation of those miRNAs affects glucose metabolism by controlling the expression of GLUT4, ameliorates PCOS-related insulin resistance, and improves PCOS-related hormonal imbalance by controlling the PI3K/AKT signaling pathway.\u003c/p\u003e","manuscriptTitle":"Do noncoding RNAs genes modulate PI3K/AKT signaling pathway in Polycystic ovary syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-04-13 22:54:27","doi":"10.21203/rs.3.rs-2756899/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revisions Needed","date":"2023-04-24T06:10:21+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2023-04-12T02:24:02+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-04-11T10:53:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-04-04T18:22:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Biology Reports","date":"2023-04-04T10:07:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d743cd74-ea10-4360-b2a2-25a8f9639098","owner":[],"postedDate":"April 13th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-09-07T15:04:45+00:00","versionOfRecord":{"articleIdentity":"rs-2756899","link":"https://doi.org/10.1007/s11033-023-08604-0","journal":{"identity":"molecular-biology-reports","isVorOnly":false,"title":"Molecular Biology Reports"},"publishedOn":"2023-08-24 15:00:58","publishedOnDateReadable":"August 24th, 2023"},"versionCreatedAt":"2023-04-13 22:54:27","video":"","vorDoi":"10.1007/s11033-023-08604-0","vorDoiUrl":"https://doi.org/10.1007/s11033-023-08604-0","workflowStages":[]},"version":"v1","identity":"rs-2756899","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2756899","identity":"rs-2756899","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}