Clinical Value of Follicular Fluid MicroRNA-21 and MicroRNA-126 Expression Profiles in Predicting Oocyte Competence and Live Birth Success

Clinical Value of Follicular Fluid MicroRNA-21 and MicroRNA-126 Expression Profiles in Predicting Oocyte Competence and Live Birth Success | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical Value of Follicular Fluid MicroRNA-21 and MicroRNA-126 Expression Profiles in Predicting Oocyte Competence and Live Birth Success Cem Dagdelen, Kuyas hekimler ozturk, Dilek Ulusoy Karatopuk, Mekin Sezik, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8828937/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Predicting the success of In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI) cycles remains a challenge. Current morphological grading systems are subjective and do not always reflect the genetic or epigenetic potential of the embryo. This study investigates whether the expression levels of miRNA-21 and miRNA-126 in follicular fluid (FF) can serve as non-invasive molecular biomarkers for predicting live birth outcomes. Methods A prospective study was conducted with 81 patients undergoing IVF/ICSI treatment. Follicular fluid samples were collected during oocyte retrieval. The expression levels of miRNA-21 and miRNA-126 were measured using quantitative real-time PCR (qRT-PCR). To address the small sample size and potential bias in live birth outcomes, Firth’s Penalized Likelihood Logistic Regression analysis was performed. Models were adjusted for maternal age and Body Mass Index (BMI). Results FF expression levels of both miRNA-21 (p = 0.034) and miRNA-126 (p = 0.038) were significantly higher in cycles that resulted in a live birth compared to those that did not. After adjusting for maternal age and BMI, both miRNAs remained independent predictors of live birth. A combined predictive model utilizing both miRNAs demonstrated an Adjusted Area Under the Curve (AUC) of 0.742, indicating a strong discriminative ability. Conclusions Increased levels of miRNA-21 and miRNA-126 in follicular fluid are associated with higher live birth rates. These microRNAs represent promising, non-invasive "liquid biopsy" biomarkers for assessing oocyte competence and predicting the clinical success of ART cycles Introduction Infertility is a global health issue that affects 10–15% of couples of reproductive age with psychosocial and economic dimensions, in addition to its medical aspects ( 1 ). Assisted Reproductive Technologies (ART), especially In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI), have brought great advances in the management of infertility; however, live birth rates per cycle are still behind targeted levels ( 2 , 3 ). The success of an IVF cycle depends on oocyte quality synchronized with the developmental potential embryo and maternal factors ( 4 ). One of the most critical steps is objectively selecting the oocyte and embryo with the highest implantation potential to sustain a healthy pregnancy until birth ( 5 ). Selection of embryos at present clinically is based largely on non-invasive morphological grading systems such as Gardner criteria ( 6 ). Morphological assessment has limitations due to inter-observer variability and inability to fully reflect genetic or epigenetic integrity of embryo ( 7 ). For example, an embryo can look morphologically perfect but may be aneuploid or metabolically insufficient ( 8 , 9 ). This situation increases the demand for new objective non-invasive molecular biomarkers that more accurately reflect competence in terms of ability to complete meiosis, fertilize successfully, and maintain embryonic development until birth ( 5 , 10 ). The competence of the oocyte for development is mainly influenced by the microenvironment of the follicle ( 11 ). Follicular fluid is a biochemical environment in dynamic equilibrium between components of plasma and secretions from cells of the follicle; it is an area where oocyte-granulosa cell bidirectional communication happens ( 4 , 12 ). FF contains large amounts of hormones, growth factors, cytokines, and metabolites that coordinate both nutrients as well as signaling pathways necessary for maturation of oocytes ( 13 , 14 ). Recent studies have been interested in epigenetic regulators found within FF, particularly microRNAs (miRNAs) ( 15 ). miRNAs are master regulators managing processes such as folliculogenesis and steroidogenesis through fine-tuning gene expression at the post-transcriptional level ( 16 ). The miRNAs chosen for this study had been previously identified as biomarker candidates because they play very important roles in processes related to oocyte maturation ( 13 , 17 ). Our miRNA-21 is a strong anti-apoptotic factor activating the PI3K/Akt signaling pathway through PTEN targeting and hence is involved in follicular survival ( 18 , 19 ). miRNA-126 is a pro-angiogenic marker that regulates vascularization and oxygen balance of follicles by controlling VEGF signaling pathways ( 20 , 21 ). There are some data available in existing literature about the relationship of these miRNAs with IVF outcome but the exact role played by variations in their expression levels towards clinical outcome has not yet been fully elucidated ( 13 , 22 ). This study seeks to find out the clinical value of follicular fluid miRNA-21 and miRNA-126 expression profiles in predicting success for live birth as well as provide a non-invasive model for assessment regarding competence of oocyte. Material and Methods Study Design and Patient Selection : This study is a single-center retrospective clinical trial assessing the data of patients treated at the Süleyman Demirel University Faculty of Medicine ART Center between January 2018 and January 2020. Ethical approval was obtained from the Süleyman Demirel University Faculty of Medicine Clinical Researches Ethics Committee (Decision No: 156, dated 07/05/2019). Based on the assumption of independent observations, only the first and single stimulation cycle for each patient was included in the analysis. The study involved fifty-two women aged 18–40 years with regular menstrual cycles and a Body Mass Index (BMI) < 35 kg/m^2. To rule out pathologies that could influence miRNA profiles, those diagnosed with PCOS, endometriosis, and POI were excluded from this study. Primary Outcome and Study Hypothesis As per local viability thresholds and registration systems, the primary endpoint of this study is a live-born infant defined as at least one live birth after 24 weeks of gestation. The primary hypothesis of the study is that FF miRNA-21 and miRNA-126 levels are significant biomarkers in predicting live birth. Granulosa cell (GC) and miRNA-17-5p parameters were analyzed secondarily and exploratorily. All embryo transfers were performed in fresh cycles. Sampling Strategy and Pre-analytical Controls During oocyte pickup (OPU), aspiration was performed from individual follicles with a diameter > 18 mm containing mature (MII) oocytes instead of pooled sampling to accurately reflect the microenvironment specific to the oocyte-follicle unit. To prevent pre-analytical variation, aspirated FF samples were spectrophotometrically checked for hemolysis (absorbance 414 nm, A414 > 0.2), and samples with detected hemolysis were excluded from the analysis. The process of clearing cellular components was achieved by centrifugation at 2,500 x g for 15 minutes. RNA Isolation and qRT-PCR Normalization Total RNA isolation was done using the miRNeasy (Qiagen) kit. U6 snRNA, which has shown stability in biofluids, served as a reference gene for normalization. Relative expression levels were calculated through fold change (2 – ∆∆Ct ) method for biological interpretation. Statistical Modeling and Validation Since data presented skewed distribution in inter-group comparisons, statistical tests were performed using log-transformed (- ∆∆Ct ) values. In logistic regression models Firth Penalized Likelihood Regression was applied to remove bias due to small sample sizes; the model was adjusted for maternal age, BMI, and transfer day (D3/D5). Model performance was evaluated by ROC analysis; AUC values were subjected to optimism correction via bootstrap (1000 iterations) method. Cut-off values were determined by Youden index. Results Baseline Clinical Characteristics No statistically significant difference was found in age, BMI, serum AMH, and AFC values between the Live Birth (+) and Live Birth (-) groups (p > 0.05, Table 1 ). Table 1 Baseline Clinical and Demographic Characteristics of the Study Group Variable Live Birth (+) (n = 14) Live Birth (-) (n = 38) p-value Maternal Age (Years) 28.00 ± 4.56 28.84 ± 4.66 0.528 BMI (kg/m^2) 25.71 ± 4.84 25.58 ± 3.95 0.852 Serum AMH (ng/mL) 3.17 ± 2.21 3.99 ± 2.82 0.415 Antral Follicle Count (AFC) 11.50 ± 3.35 10.63 ± 3.45 0.435 FF and GC miRNA Expression Levels As a result of the analyses, FF miRNA-21 (p = 0.034) and miRNA-126 (p = 0.038) levels, included in the primary hypothesis, were found to be significantly higher in the live birth group. Descriptive statistics are presented via fold change in Table 2 , while p-values were obtained from normalized logarithmic values. Table 2 Relative miRNA Expression Levels by Sample Types ( 2 – ∆∆Ct ) miRNA Parameter Live Birth (+) (n = 14) Mean ± SD Live Birth (-) (n = 38) Mean ± SD p-value* miRNA-21 (FF) 1.46 ± 1.09 1.07 ± 1.16 0.034 miRNA-126 (FF) 5.25 ± 4.13 3.76 ± 5.52 0.038 miRNA-17-5p (FF) 2.26 ± 2.96 1.56 ± 2.53 0.140 miRNA-21 (GC) 1.14 ± 1.34 0.84 ± 0.92 0.334 miRNA-126 (GC) 0.89 ± 1.45 0.76 ± 0.88 0.452 *Statistical significance testing was performed on log2-transformed (- ∆∆Ct ) values. Modeling and Discriminative Power In adjusted Firth regression models, miRNA-21 and miRNA-126 levels were identified as independent predictors of live birth. The combined model (miRNA-21 + miRNA-126) exhibited promising discriminative power (Table 3 ). Table 3 Firth Logistic Regression and Validation Results in Predicting Live Birth Predictive Variable (FF) Adjusted OR (95% CI) p-value Bootstrap Adjusted AUC miRNA-21 (Log2FC) 2.62 (1.18–5.81) 0.019 0.672 miRNA-126 (Log2FC) 1.95 (1.09–3.50) 0.026 0.665 Combined Model* 3.38 (1.55–7.42) 0.002 0.742 *The combined model OR value was calculated based on a 1-standard deviation increase in the panel risk score (linear predictor). Discussion This study revealed that the expression profiles of miRNA-21 and miRNA-126 in follicular fluid are promising molecular biomarkers for oocyte competence and live birth success in assisted reproductive technologies ( 11 , 13 , 22 ). Although our findings closely parallel those of pioneering hypotheses attempting to define oocyte quality at the molecular level, they uniquely position themselves by proving the effect on clinical outcomes through independent variables ( 13 , 23 ). When comparing results with existing data in the literature, studies by Machtinger et al. have shown that miRNAs packaged in extracellular vesicles within the FF are directly related to fertilization success and embryo quality. The transport of miRNAs within vesicles rather than free form in FF makes them stable and reliable "liquid biopsy" materials by protecting from RNase enzymes ( 11 , 22 ). While intracellular levels of miRNA reflect instantaneous transcriptional fluctuations, FF vesicles provide a cumulative molecular record about an entire developmental process of an oocyte ( 11 , 24 ). The significantly higher levels of FF miRNA-21 observed in successful cycles resulting in live birth (p = 0.034) further underscore the pivotal role that this molecule plays in follicular survival ( 18 , 25 ). miRNA-21 activates the PI3K/Akt signaling pathway by inhibiting its main target, PTEN protein. It supports oocyte development by preventing apoptosis in granulosa cells ( 25 , 26 ). Moreover, it is known that miRNA-21 creates an "apoptotic quenching" effect through reducing cleaved caspase-3 levels which helps nuclear maturation of the oocyte ( 22 , 27 ). Wright et al., underscoring the evolutionary conserved importance of this mechanism demonstrated a 25-fold increase of miRNA-21 in cumulus cells during maturation of porcine oocytes ( 28 ). The strong negative correlation between maternal age and FF miRNA-21 found in this study (r = -0.403) supports the findings of Battaglia et al. ( 29 , 30 ) when linked to live birth outcomes. Decreasing levels of miRNA-21 with increasing age may reduce reproductive success by leading to disruption of mitochondrial integrity (mitomiR) leaving oocytes unprotected against oxidative damage ( 30 , 31 ). The high level of miRNA-126 in successful cycles (p = 0.038) further validates the very important role that follicular vascularization plays in the development of an oocyte through angiogenesis/VEGF axis signaling pathway activity ( 20 , 32 ). It optimizes pro-angiogenic response via a "suppressing the suppressors" strategy by inhibiting SPRED1 and PIK3R2 proteins, which are negative regulators of VEGF signaling pathway ( 21 , 32 ). Although Santonocito et al. ( 13 , 33 ) proposed that FF miRNA signatures are strong tools reflecting oocyte quality, the true function of angiogenic markers has remained debatable in literature; however, our study supports the theory that miRNA-126 as a "precision modulator" maintains ideal oxygen balance within follicle and decreases aneuploidy risk due to hypoxic stress during meiotic division ( 21 , 32 ). The reason why significant differences were found only in follicular fluid but not in granulosa cells is that FF represents more stably the specific microenvironment of the oocyte-follicle unit compared to cells ( 23 ). In our results, the lack of difference found for GC may be due to cellular miRNA profiles instantaneously fluctuating or stable representation through vesicular accumulation in FF dynamic communication within oocyte microenvironment ( 13 , 34 ). This situation proves diagnostic superiority for FF as a "liquid biopsy" material over cellular biopsies. The Adjusted AUC (0.742) value shown by the miRNA panel developed in this study for predicting live birth indicates promising discriminative power applicable clinically; however, it should also be noted that this is a single-center study with few events—primary limitations. Broader and multicenter prospective validation studies will be required before such detected AUC values can translate into definitive clinical cut-off values. Although there is some controversy over stability regarding U6 snRNA normalization in biofluids per literature ( 35 ), one strength increasing reliability for our study results is meticulous pre-analytical control concerning hemolysis. Study Limitations Although our cohort of 52 cases yielded significant results, for the AUC values that we have found to be significant to be applicable as clinical cut-off values wider and multicenter prospective studies will be necessary. Also, the controversial stability of U6 snRNA which is widely used in miRNA normalization still remains an issue on standardization in the literature. Future studies with exogenous spike-in controls and careful hemolysis control would increase reproducibility. Conclusion Data from this study suggest that profiles of follicular fluid miRNA-21 and miRNA-126 are functional noninvasive biomarkers clinically relevant for prediction of live birth in IVF/ICSI cycles with promising clinically significant discriminative power. Declarations Ethics approval and consent to participate Ethical approval was granted by the Süleyman Demirel University Faculty of Medicine Clinical Researches Ethics Committee (Date: May 7, 2019; Decision No: 156). Informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by the Süleyman Demirel University Scientific Research Projects Coordination Unit (BAP) under project number TTU-2020-7497. Authors' contributions CD: Conceptualization, Methodology, Formal analysis, Writing – original draft. KHÖ: Methodology, Validation. DUK: Investigation, Resources. MS: Supervision, Writing – review & editing. GB: Conceptualization, Funding acquisition, Supervision. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Zegers-Hochschild F, Adamson GD, Dyer S, et al. The International Glossary on Infertility and Fertility Care, 2017. Hum Reprod. 2017;32(9):1786–801. Vander Borght M, Wyns C. Fertility and infertility: Definition and epidemiology. Clin Biochem. 2018;62:2–10. de Mouzon J, Goossens V, Bhattacharya S, et al. Assisted reproductive technology in Europe, 2016: results generated from European registers by ESHRE. Hum Reprod Open. 2020;2020(3):hoaa032. Da Broi MG, Giorgi VSI, Wang F, et al. Influence of follicular fluid and cumulus cells on oocyte quality. J Assist Reprod Genet. 2018;35(5):739–51. Sciorio R, Miranian D, Smith GD. Non-invasive oocyte quality assessment. Biol Reprod. 2022;106(2):274–90. Gardner DK, Schoolcraft WB. In vitro culture of human blastocysts. Towards Reproductive Certainty. 1999;378–88. Lemseffer N, Sirait B, et al. Subjectivity and inherent limitations in oocyte morphology assessment. Middle East Fertil Soc J. 2022;27:14. Capalbo A, et al. Correlation between morphokinetics and chromosomal status in human blastocysts. Hum Reprod. 2014;29(6):1173–81. Juneau C, et al. The challenges of invasive embryo biopsy and mosaicism. J Assist Reprod Genet. 2016;33(10):1317–23. Fischer PS, et al. Identifying potential biomarkers in follicular fluid for oocyte quality assessment. J Bras Reprod Assist. 2021;25(4):595–603. Machtinger R, Laurent LC, Baccarelli AA. Extracellular microRNAs profile in human follicular fluid and IVF outcomes. Sci Rep. 2017;7(1):15172. Strauss JF, Barbieri RL, editors. Yen & Jaffe's Reproductive Endocrinology: Physiology, Pathophysiology, and Clinical Management. 9th ed. Philadelphia: Elsevier; 2023. Santonocito M, et al. Circulating microRNAs in follicular fluid, powerful tools to explore in vitro fertilization process. Sci Rep. 2014;4:5455. Lazzarino G, et al. Altered Follicular Fluid Metabolic Pattern Correlates with Female Infertility and IVF. Int J Mol Sci. 2021;22(16):8735. Tesfaye D. MicroRNAs: tiny molecules with a significant role in mammalian follicular and oocyte development. Reproduction. 2018;155(3):R121–34. Hossain MM, et al. Regulation of oocyte maturation and follicular growth by miRNAs. J Assist Reprod Genet. 2012;29(8):799–808. Sang Q, et al. Identification of microRNAs in human follicular fluid and their roles in steroidogenesis. J Assist Reprod Genet. 2013;30(3):333–9. Wright EC, et al. Evaluation of the potential of miR-21 as a diagnostic marker for oocyte maturity and embryo quality in ICSI. Sci Rep. 2023;13(1):1440. Makker A, et al. PI3K/PTEN/Akt and TSC/mTOR signaling pathways: critical regulators of ovarian function. J Mol Endocrinol. 2014;53(3):R103–18. Brzoska-Wojt E et al. MicroRNA-126: A key regulator of angiogenesis and vascular health. Biochim Biophys Acta Mol Basis Dis. 2025;167984. Wang S, et al. The Endothelial-Specific MicroRNA miR-126 Governs Vascular Integrity and Angiogenesis. Dev Cell. 2008;15(2):261–71. Almutlaq A. Understanding the molecular differences between good- and poor-quality embryos through miRNA expression. UCL Doctoral Thesis; 2021. Machtinger R, et al. Encapsulated microRNAs (EV-miRNAs) in follicular fluid: IVF cycle associations. Sci Rep. 2018;8(1):16122. Dissanayake V, et al. The role of extracellular vesicles as biomarkers for fertility assessment. Reprod Biol Endocrinol. 2021;19(1):147. Dehghan Z, et al. MicroRNA-21 is involved in oocyte maturation, blastocyst formation, and pre-implantation embryo development. Dev Biol. 2021;480:69–77. Han L, et al. MicroRNA-21 inhibits apoptosis of granulosa cells by targeting PTEN/PI3K/Akt signaling pathway. Cell Cycle. 2017;16(21):2100–10. Pan B, Li J. The biological function of microRNA-21 in mammalian reproduction. Front Cell Dev Biol. 2023;11:1294541. Wright EC, et al. MIR21 expression is temporally regulated during porcine cumulus oocyte complex maturation. Sci Rep. 2023;13(1):1440. Battaglia R, et al. Ovarian aging increases small extracellular vesicle release in human follicular fluid and influences miRNA profiles. Aging. 2020;12(10):9523–48. Purrello M, et al. Resveratrol Treatment Induces Mito-miRNome Modification in aged women with poor ovarian reserve. Aging. 2022;14(11):4641–63. Nejabati HR, et al. Follicular Fluid Extracellular Vesicle miRNAs and Ovarian Aging. Clin Chim Acta. 2022;537:126–35. Fish JE, et al. miR-126 regulates angiogenic signaling and vascular integrity. Dev Cell. 2008;15(2):272–84. Santonocito M, et al. Follicular fluid miRNA signatures as indicators of oocyte quality. J Assist Reprod Genet. 2014;31(11):1477–84. Rooda I, et al. miRNA profiles in FF EVs differ significantly from somatic follicular cells and bulk FF. Int J Mol Sci. 2020;21(24):9550. Varkonyi J, et al. Challenges of U6 snRNA as a normalization control in miRNA studies. PLoS ONE. 2023;18(3):e0282576. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8828937","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594806290,"identity":"762c951a-b1bf-418a-95e0-cec9a12abf72","order_by":0,"name":"Cem Dagdelen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYHACAwYGNgYZBgbmA0COhAzRWniARAJICw8pWngMQDzCWvinHd748UuZDQ+/dM/nVzdqLHgY2A8f3YBPi8TttGJpmXNpPJJzzm6zzjkGdBhPWtoNvK6SzjGQlmw7zGNwI3ebcQ4bUIsEjxkhLca/Jdv+89jfyHlmnPOPOC1mkh/bDvAYSOQwP85tI0IL0C9l1gznknkkbqSZMef2SfCwEfIL/+zkzTd/lNnJ8c9Ifvw551udHD/74WN4tYAAMzQu2CTAJCHlIMD4A6r1AzGqR8EoGAWjYOQBAFHGQrHLKGRXAAAAAElFTkSuQmCC","orcid":"","institution":"Akdeniz University","correspondingAuthor":true,"prefix":"","firstName":"Cem","middleName":"","lastName":"Dagdelen","suffix":""},{"id":594806291,"identity":"5968dd37-93db-4f0b-bd5f-b49c7de86995","order_by":1,"name":"Kuyas hekimler ozturk","email":"","orcid":"","institution":"Süleyman Demirel University","correspondingAuthor":false,"prefix":"","firstName":"Kuyas","middleName":"hekimler","lastName":"ozturk","suffix":""},{"id":594806292,"identity":"0bc69251-6ee1-4ebb-97c4-ca20d6ecbc36","order_by":2,"name":"Dilek Ulusoy Karatopuk","email":"","orcid":"","institution":"Süleyman Demirel University","correspondingAuthor":false,"prefix":"","firstName":"Dilek","middleName":"Ulusoy","lastName":"Karatopuk","suffix":""},{"id":594806293,"identity":"e27256fa-5b9e-4d12-87a4-a4efaeea19c3","order_by":3,"name":"Mekin Sezik","email":"","orcid":"","institution":"Süleyman Demirel University","correspondingAuthor":false,"prefix":"","firstName":"Mekin","middleName":"","lastName":"Sezik","suffix":""},{"id":594806294,"identity":"0d5c868b-9264-4703-baec-9c0f7f5d67a0","order_by":4,"name":"Gokhan Bayhan","email":"","orcid":"","institution":"Süleyman Demirel University","correspondingAuthor":false,"prefix":"","firstName":"Gokhan","middleName":"","lastName":"Bayhan","suffix":""}],"badges":[],"createdAt":"2026-02-09 10:09:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8828937/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8828937/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105727774,"identity":"2ddad971-a276-4c0b-a69b-73ec7a736971","added_by":"auto","created_at":"2026-03-30 11:03:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":642502,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8828937/v1/76373e21-0a92-4856-a0b2-5cad8471b80a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Value of Follicular Fluid MicroRNA-21 and MicroRNA-126 Expression Profiles in Predicting Oocyte Competence and Live Birth Success","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInfertility is a global health issue that affects 10\u0026ndash;15% of couples of reproductive age with psychosocial and economic dimensions, in addition to its medical aspects (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Assisted Reproductive Technologies (ART), especially In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI), have brought great advances in the management of infertility; however, live birth rates per cycle are still behind targeted levels (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The success of an IVF cycle depends on oocyte quality synchronized with the developmental potential embryo and maternal factors (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). One of the most critical steps is objectively selecting the oocyte and embryo with the highest implantation potential to sustain a healthy pregnancy until birth (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Selection of embryos at present clinically is based largely on non-invasive morphological grading systems such as Gardner criteria (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Morphological assessment has limitations due to inter-observer variability and inability to fully reflect genetic or epigenetic integrity of embryo (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). For example, an embryo can look morphologically perfect but may be aneuploid or metabolically insufficient (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). This situation increases the demand for new objective non-invasive molecular biomarkers that more accurately reflect competence in terms of ability to complete meiosis, fertilize successfully, and maintain embryonic development until birth (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe competence of the oocyte for development is mainly influenced by the microenvironment of the follicle (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Follicular fluid is a biochemical environment in dynamic equilibrium between components of plasma and secretions from cells of the follicle; it is an area where oocyte-granulosa cell bidirectional communication happens (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). FF contains large amounts of hormones, growth factors, cytokines, and metabolites that coordinate both nutrients as well as signaling pathways necessary for maturation of oocytes (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Recent studies have been interested in epigenetic regulators found within FF, particularly microRNAs (miRNAs) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). miRNAs are master regulators managing processes such as folliculogenesis and steroidogenesis through fine-tuning gene expression at the post-transcriptional level (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The miRNAs chosen for this study had been previously identified as biomarker candidates because they play very important roles in processes related to oocyte maturation (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Our miRNA-21 is a strong anti-apoptotic factor activating the PI3K/Akt signaling pathway through PTEN targeting and hence is involved in follicular survival (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). miRNA-126 is a pro-angiogenic marker that regulates vascularization and oxygen balance of follicles by controlling VEGF signaling pathways (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). There are some data available in existing literature about the relationship of these miRNAs with IVF outcome but the exact role played by variations in their expression levels towards clinical outcome has not yet been fully elucidated (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study seeks to find out the clinical value of follicular fluid miRNA-21 and miRNA-126 expression profiles in predicting success for live birth as well as provide a non-invasive model for assessment regarding competence of oocyte.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e \u003cb\u003eStudy Design and Patient Selection\u003c/b\u003e: This study is a single-center retrospective clinical trial assessing the data of patients treated at the S\u0026uuml;leyman Demirel University Faculty of Medicine ART Center between January 2018 and January 2020. Ethical approval was obtained from the S\u0026uuml;leyman Demirel University Faculty of Medicine Clinical Researches Ethics Committee (Decision No: 156, dated 07/05/2019). Based on the assumption of independent observations, only the first and single stimulation cycle for each patient was included in the analysis. The study involved fifty-two women aged 18\u0026ndash;40 years with regular menstrual cycles and a Body Mass Index (BMI)\u0026thinsp;\u0026lt;\u0026thinsp;35 kg/m^2. To rule out pathologies that could influence miRNA profiles, those diagnosed with PCOS, endometriosis, and POI were excluded from this study.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePrimary Outcome and Study Hypothesis\u003c/strong\u003e \u003cp\u003eAs per local viability thresholds and registration systems, the primary endpoint of this study is a live-born infant defined as at least one live birth after 24 weeks of gestation. The primary hypothesis of the study is that FF miRNA-21 and miRNA-126 levels are significant biomarkers in predicting live birth. Granulosa cell (GC) and miRNA-17-5p parameters were analyzed secondarily and exploratorily. All embryo transfers were performed in fresh cycles.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSampling Strategy and Pre-analytical Controls\u003c/strong\u003e \u003cp\u003eDuring oocyte pickup (OPU), aspiration was performed from individual follicles with a diameter\u0026thinsp;\u0026gt;\u0026thinsp;18 mm containing mature (MII) oocytes instead of pooled sampling to accurately reflect the microenvironment specific to the oocyte-follicle unit. To prevent pre-analytical variation, aspirated FF samples were spectrophotometrically checked for hemolysis (absorbance 414 nm, A414\u0026thinsp;\u0026gt;\u0026thinsp;0.2), and samples with detected hemolysis were excluded from the analysis. The process of clearing cellular components was achieved by centrifugation at 2,500 x g for 15 minutes.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRNA Isolation and qRT-PCR Normalization\u003c/h2\u003e \u003cp\u003eTotal RNA isolation was done using the miRNeasy (Qiagen) kit. U6 snRNA, which has shown stability in biofluids, served as a reference gene for normalization. Relative expression levels were calculated through fold change (2 \u003csup\u003e\u0026ndash; ∆∆Ct\u003c/sup\u003e ) method for biological interpretation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Modeling and Validation\u003c/h3\u003e\n\u003cp\u003eSince data presented skewed distribution in inter-group comparisons, statistical tests were performed using log-transformed (- \u003cem\u003e∆∆Ct\u003c/em\u003e ) values. In logistic regression models Firth Penalized Likelihood Regression was applied to remove bias due to small sample sizes; the model was adjusted for maternal age, BMI, and transfer day (D3/D5). Model performance was evaluated by ROC analysis; AUC values were subjected to optimism correction via bootstrap (1000 iterations) method. Cut-off values were determined by Youden index.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cstrong\u003eBaseline Clinical Characteristics\u003c/strong\u003e \u003cp\u003eNo statistically significant difference was found in age, BMI, serum AMH, and AFC values between the Live Birth (+) and Live Birth (-) groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Clinical and Demographic Characteristics of the Study Group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive Birth (+) (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLive Birth (-) (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Age (Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e28.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e28.84\u0026thinsp;\u0026plusmn;\u0026thinsp;4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m^2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.71\u0026thinsp;\u0026plusmn;\u0026thinsp;4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum AMH (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.99\u0026thinsp;\u0026plusmn;\u0026thinsp;2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntral Follicle Count (AFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e11.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.63\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFF and GC miRNA Expression Levels\u003c/strong\u003e \u003cp\u003eAs a result of the analyses, FF miRNA-21 (p\u0026thinsp;=\u0026thinsp;0.034) and miRNA-126 (p\u0026thinsp;=\u0026thinsp;0.038) levels, included in the primary hypothesis, were found to be significantly higher in the live birth group. Descriptive statistics are presented via fold change in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, while p-values were obtained from normalized logarithmic values.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelative miRNA Expression Levels by Sample Types \u003cb\u003e(\u003c/b\u003e2 \u003csup\u003e\u0026ndash; ∆∆Ct\u003c/sup\u003e \u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA Parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive Birth (+) (n\u0026thinsp;=\u0026thinsp;14) Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLive Birth (-) (n\u0026thinsp;=\u0026thinsp;38) Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA-21 (FF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA-126 (FF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.25\u0026thinsp;\u0026plusmn;\u0026thinsp;4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.76\u0026thinsp;\u0026plusmn;\u0026thinsp;5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA-17-5p (FF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA-21 (GC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA-126 (GC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Statistical significance testing was performed on log2-transformed (- \u003cem\u003e∆∆Ct\u003c/em\u003e ) values.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eModeling and Discriminative Power\u003c/strong\u003e \u003cp\u003eIn adjusted Firth regression models, miRNA-21 and miRNA-126 levels were identified as independent predictors of live birth. The combined model (miRNA-21\u0026thinsp;+\u0026thinsp;miRNA-126) exhibited promising discriminative power (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFirth Logistic Regression and Validation Results in Predicting Live Birth\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictive Variable (FF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBootstrap Adjusted AUC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA-21 (Log2FC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.62 (1.18\u0026ndash;5.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiRNA-126 (Log2FC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.95 (1.09\u0026ndash;3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined Model*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.38 (1.55\u0026ndash;7.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*The combined model OR value was calculated based on a 1-standard deviation increase in the panel risk score (linear predictor).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study revealed that the expression profiles of miRNA-21 and miRNA-126 in follicular fluid are promising molecular biomarkers for oocyte competence and live birth success in assisted reproductive technologies (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Although our findings closely parallel those of pioneering hypotheses attempting to define oocyte quality at the molecular level, they uniquely position themselves by proving the effect on clinical outcomes through independent variables (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). When comparing results with existing data in the literature, studies by Machtinger et al. have shown that miRNAs packaged in extracellular vesicles within the FF are directly related to fertilization success and embryo quality. The transport of miRNAs within vesicles rather than free form in FF makes them stable and reliable \"liquid biopsy\" materials by protecting from RNase enzymes (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). While intracellular levels of miRNA reflect instantaneous transcriptional fluctuations, FF vesicles provide a cumulative molecular record about an entire developmental process of an oocyte (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe significantly higher levels of FF miRNA-21 observed in successful cycles resulting in live birth (p\u0026thinsp;=\u0026thinsp;0.034) further underscore the pivotal role that this molecule plays in follicular survival (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). miRNA-21 activates the PI3K/Akt signaling pathway by inhibiting its main target, PTEN protein. It supports oocyte development by preventing apoptosis in granulosa cells (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Moreover, it is known that miRNA-21 creates an \"apoptotic quenching\" effect through reducing cleaved caspase-3 levels which helps nuclear maturation of the oocyte (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Wright et al., underscoring the evolutionary conserved importance of this mechanism demonstrated a 25-fold increase of miRNA-21 in cumulus cells during maturation of porcine oocytes (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe strong negative correlation between maternal age and FF miRNA-21 found in this study (r = -0.403) supports the findings of Battaglia et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) when linked to live birth outcomes. Decreasing levels of miRNA-21 with increasing age may reduce reproductive success by leading to disruption of mitochondrial integrity (mitomiR) leaving oocytes unprotected against oxidative damage (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The high level of miRNA-126 in successful cycles (p\u0026thinsp;=\u0026thinsp;0.038) further validates the very important role that follicular vascularization plays in the development of an oocyte through angiogenesis/VEGF axis signaling pathway activity (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). It optimizes pro-angiogenic response via a \"suppressing the suppressors\" strategy by inhibiting SPRED1 and PIK3R2 proteins, which are negative regulators of VEGF signaling pathway (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Although Santonocito et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) proposed that FF miRNA signatures are strong tools reflecting oocyte quality, the true function of angiogenic markers has remained debatable in literature; however, our study supports the theory that miRNA-126 as a \"precision modulator\" maintains ideal oxygen balance within follicle and decreases aneuploidy risk due to hypoxic stress during meiotic division (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe reason why significant differences were found only in follicular fluid but not in granulosa cells is that FF represents more stably the specific microenvironment of the oocyte-follicle unit compared to cells (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In our results, the lack of difference found for GC may be due to cellular miRNA profiles instantaneously fluctuating or stable representation through vesicular accumulation in FF dynamic communication within oocyte microenvironment (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). This situation proves diagnostic superiority for FF as a \"liquid biopsy\" material over cellular biopsies. The Adjusted AUC (0.742) value shown by the miRNA panel developed in this study for predicting live birth indicates promising discriminative power applicable clinically; however, it should also be noted that this is a single-center study with few events\u0026mdash;primary limitations. Broader and multicenter prospective validation studies will be required before such detected AUC values can translate into definitive clinical cut-off values. Although there is some controversy over stability regarding U6 snRNA normalization in biofluids per literature (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), one strength increasing reliability for our study results is meticulous pre-analytical control concerning hemolysis.\u003c/p\u003e"},{"header":"Study Limitations","content":"\u003cp\u003eAlthough our cohort of 52 cases yielded significant results, for the AUC values that we have found to be significant to be applicable as clinical cut-off values wider and multicenter prospective studies will be necessary. Also, the controversial stability of U6 snRNA which is widely used in miRNA normalization still remains an issue on standardization in the literature. Future studies with exogenous spike-in controls and careful hemolysis control would increase reproducibility.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eData from this study suggest that profiles of follicular fluid miRNA-21 and miRNA-126 are functional noninvasive biomarkers clinically relevant for prediction of live birth in IVF/ICSI cycles with promising clinically significant discriminative power.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e Ethical approval was granted by the S\u0026uuml;leyman Demirel University Faculty of Medicine Clinical Researches Ethics Committee (Date: May 7, 2019; Decision No: 156). Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This study was supported by the S\u0026uuml;leyman Demirel University Scientific Research Projects Coordination Unit (BAP) under project number TTU-2020-7497.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e CD: Conceptualization, Methodology, Formal analysis, Writing \u0026ndash; original draft. KH\u0026Ouml;: Methodology, Validation. DUK: Investigation, Resources. MS: Supervision, Writing \u0026ndash; review \u0026amp; editing. GB: Conceptualization, Funding acquisition, Supervision. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZegers-Hochschild F, Adamson GD, Dyer S, et al. The International Glossary on Infertility and Fertility Care, 2017. Hum Reprod. 2017;32(9):1786\u0026ndash;801.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVander Borght M, Wyns C. Fertility and infertility: Definition and epidemiology. Clin Biochem. 2018;62:2\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Mouzon J, Goossens V, Bhattacharya S, et al. Assisted reproductive technology in Europe, 2016: results generated from European registers by ESHRE. Hum Reprod Open. 2020;2020(3):hoaa032.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDa Broi MG, Giorgi VSI, Wang F, et al. Influence of follicular fluid and cumulus cells on oocyte quality. J Assist Reprod Genet. 2018;35(5):739\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSciorio R, Miranian D, Smith GD. Non-invasive oocyte quality assessment. Biol Reprod. 2022;106(2):274\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGardner DK, Schoolcraft WB. In vitro culture of human blastocysts. Towards Reproductive Certainty. 1999;378\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLemseffer N, Sirait B, et al. Subjectivity and inherent limitations in oocyte morphology assessment. Middle East Fertil Soc J. 2022;27:14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCapalbo A, et al. Correlation between morphokinetics and chromosomal status in human blastocysts. Hum Reprod. 2014;29(6):1173\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuneau C, et al. The challenges of invasive embryo biopsy and mosaicism. J Assist Reprod Genet. 2016;33(10):1317\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFischer PS, et al. Identifying potential biomarkers in follicular fluid for oocyte quality assessment. J Bras Reprod Assist. 2021;25(4):595\u0026ndash;603.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMachtinger R, Laurent LC, Baccarelli AA. Extracellular microRNAs profile in human follicular fluid and IVF outcomes. Sci Rep. 2017;7(1):15172.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrauss JF, Barbieri RL, editors. Yen \u0026amp; Jaffe's Reproductive Endocrinology: Physiology, Pathophysiology, and Clinical Management. 9th ed. Philadelphia: Elsevier; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantonocito M, et al. Circulating microRNAs in follicular fluid, powerful tools to explore in vitro fertilization process. Sci Rep. 2014;4:5455.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLazzarino G, et al. Altered Follicular Fluid Metabolic Pattern Correlates with Female Infertility and IVF. Int J Mol Sci. 2021;22(16):8735.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTesfaye D. MicroRNAs: tiny molecules with a significant role in mammalian follicular and oocyte development. Reproduction. 2018;155(3):R121\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHossain MM, et al. Regulation of oocyte maturation and follicular growth by miRNAs. J Assist Reprod Genet. 2012;29(8):799\u0026ndash;808.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSang Q, et al. Identification of microRNAs in human follicular fluid and their roles in steroidogenesis. J Assist Reprod Genet. 2013;30(3):333\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWright EC, et al. Evaluation of the potential of miR-21 as a diagnostic marker for oocyte maturity and embryo quality in ICSI. Sci Rep. 2023;13(1):1440.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMakker A, et al. PI3K/PTEN/Akt and TSC/mTOR signaling pathways: critical regulators of ovarian function. J Mol Endocrinol. 2014;53(3):R103\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrzoska-Wojt E et al. MicroRNA-126: A key regulator of angiogenesis and vascular health. Biochim Biophys Acta Mol Basis Dis. 2025;167984.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang S, et al. The Endothelial-Specific MicroRNA miR-126 Governs Vascular Integrity and Angiogenesis. Dev Cell. 2008;15(2):261\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlmutlaq A. Understanding the molecular differences between good- and poor-quality embryos through miRNA expression. UCL Doctoral Thesis; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMachtinger R, et al. Encapsulated microRNAs (EV-miRNAs) in follicular fluid: IVF cycle associations. Sci Rep. 2018;8(1):16122.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDissanayake V, et al. The role of extracellular vesicles as biomarkers for fertility assessment. Reprod Biol Endocrinol. 2021;19(1):147.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehghan Z, et al. MicroRNA-21 is involved in oocyte maturation, blastocyst formation, and pre-implantation embryo development. Dev Biol. 2021;480:69\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan L, et al. MicroRNA-21 inhibits apoptosis of granulosa cells by targeting PTEN/PI3K/Akt signaling pathway. Cell Cycle. 2017;16(21):2100\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan B, Li J. The biological function of microRNA-21 in mammalian reproduction. Front Cell Dev Biol. 2023;11:1294541.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWright EC, et al. MIR21 expression is temporally regulated during porcine cumulus oocyte complex maturation. Sci Rep. 2023;13(1):1440.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBattaglia R, et al. Ovarian aging increases small extracellular vesicle release in human follicular fluid and influences miRNA profiles. Aging. 2020;12(10):9523\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePurrello M, et al. Resveratrol Treatment Induces Mito-miRNome Modification in aged women with poor ovarian reserve. Aging. 2022;14(11):4641\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNejabati HR, et al. Follicular Fluid Extracellular Vesicle miRNAs and Ovarian Aging. Clin Chim Acta. 2022;537:126\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFish JE, et al. miR-126 regulates angiogenic signaling and vascular integrity. Dev Cell. 2008;15(2):272\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantonocito M, et al. Follicular fluid miRNA signatures as indicators of oocyte quality. J Assist Reprod Genet. 2014;31(11):1477\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRooda I, et al. miRNA profiles in FF EVs differ significantly from somatic follicular cells and bulk FF. Int J Mol Sci. 2020;21(24):9550.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVarkonyi J, et al. Challenges of U6 snRNA as a normalization control in miRNA studies. PLoS ONE. 2023;18(3):e0282576.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8828937/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8828937/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePredicting the success of In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI) cycles remains a challenge. Current morphological grading systems are subjective and do not always reflect the genetic or epigenetic potential of the embryo. This study investigates whether the expression levels of miRNA-21 and miRNA-126 in follicular fluid (FF) can serve as non-invasive molecular biomarkers for predicting live birth outcomes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA prospective study was conducted with 81 patients undergoing IVF/ICSI treatment. Follicular fluid samples were collected during oocyte retrieval. The expression levels of miRNA-21 and miRNA-126 were measured using quantitative real-time PCR (qRT-PCR). To address the small sample size and potential bias in live birth outcomes, Firth\u0026rsquo;s Penalized Likelihood Logistic Regression analysis was performed. Models were adjusted for maternal age and Body Mass Index (BMI).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFF expression levels of both miRNA-21 (p\u0026thinsp;=\u0026thinsp;0.034) and miRNA-126 (p\u0026thinsp;=\u0026thinsp;0.038) were significantly higher in cycles that resulted in a live birth compared to those that did not. After adjusting for maternal age and BMI, both miRNAs remained independent predictors of live birth. A combined predictive model utilizing both miRNAs demonstrated an Adjusted Area Under the Curve (AUC) of 0.742, indicating a strong discriminative ability.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIncreased levels of miRNA-21 and miRNA-126 in follicular fluid are associated with higher live birth rates. These microRNAs represent promising, non-invasive \"liquid biopsy\" biomarkers for assessing oocyte competence and predicting the clinical success of ART cycles\u003c/p\u003e","manuscriptTitle":"Clinical Value of Follicular Fluid MicroRNA-21 and MicroRNA-126 Expression Profiles in Predicting Oocyte Competence and Live Birth Success","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 16:55:06","doi":"10.21203/rs.3.rs-8828937/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d13dde1-6858-4219-b33b-015e0f416dd3","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T08:58:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 16:55:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8828937","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8828937","identity":"rs-8828937","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}