Association of Oxidative Stress and Advanced Glycation End Products with Uterine Fibroids in Women of Reproductive Age: a Retrospective Observational Study

Association of Oxidative Stress and Advanced Glycation End Products with Uterine Fibroids in Women of Reproductive Age: a Retrospective Observational Study | 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 Association of Oxidative Stress and Advanced Glycation End Products with Uterine Fibroids in Women of Reproductive Age: a Retrospective Observational Study Takuji Nishihara, Yusaku Mori, Kuniaki Ota, Fumiyuki Isami, Sho-Ichi Yamagishi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9217861/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Uterine fibroids are common benign tumors in reproductive-age women and substantially impair quality of life. Advanced glycation end products (AGEs) have been implicated in ovarian disorders through oxidative stress, but their involvement in uterine fibroids remains unclear. This study aimed to examine the associations between AGE accumulation, oxidative stress, and uterine fibroids. Methods This retrospective observational study included 75 women undergoing infertility treatment between 2015 and 2018. AGE accumulation was assessed using skin autofluorescence (SAF). Serum diacron-reactive oxygen metabolites (d-ROMs) were measured as an index of oxidative stress, along with biochemical and reproductive hormone parameters. Associations with uterine fibroids were evaluated using logistic regression, elastic-net–regularized variable selection, and exploratory mediation analysis. Results Women with uterine fibroids exhibited significantly higher SAF and d-ROMs levels than women without gynecological disease. Both SAF and d-ROMs were associated with uterine fibroids in univariable analyses. However, in multivariable logistic regression, only d-ROMs remained independently associated with uterine fibroids. Exploratory mediation analysis suggested that d-ROMs statistically explained 46% of the association between SAF and uterine fibroids. Conclusions The present findings suggest that oxidative stress may be associated with uterine fibroids in women of reproductive age and may represent a potential biological correlate linking AGE accumulation to uterine fibroids. Advanced glycation end products skin autofluorescence oxidative stress uterine fibroids Figures Figure 1 1. Background Uterine fibroids are common benign uterine tumors in women of reproductive age and represent a major cause of pelvic pain, abnormal uterine bleeding, infertility, and impaired quality of life [ 1 ]. Epidemiological studies have reported that metabolic derangements and unhealthy lifestyle habits, including obesity, alcohol consumption, and smoking, are associated with uterine fibroids [ 2 , 3 ]. However, despite their substantial clinical burden, the biological mechanisms linking systemic metabolic disturbances and lifestyle factors to fibroid development remain incompletely understood. Advanced glycation end products (AGEs) are heterogeneous macromolecular adducts formed through nonenzymatic reactions between monosaccharides and amino groups of proteins, lipids, and nucleic acids [ 4 ]. Endogenous AGE formation is accelerated under conditions such as diabetes, obesity, and aging, while dietary intake represents an important source of exogenous AGEs in humans [ 4 ]. Accumulating evidence suggests that AGEs activate inflammatory and oxidative pathways in multiple tissues via interaction with the receptor for AGEs (RAGE), thereby contributing to the pathogenesis of various chronic noncommunicable diseases [ 4 ]. Because several AGE species exhibit autofluorescence, systemic AGE accumulation can be noninvasively assessed using skin autofluorescence (SAF) [ 5 ]. SAF has been shown to correlate with tissue accumulation of both fluorescent and nonfluorescent AGEs, and skin AGE content has been reported to account for approximately 76% of the variance in SAF, supporting its use as a surrogate biomarker of cumulative metabolic stress- and lifestyle-related AGE accumulation [ 5 , 6 ]. Previous studies have demonstrated associations between elevated SAF and adverse clinical outcomes, including cardiovascular disease, cancer, and all-cause mortality, in both diabetic and non-diabetic populations [ 7 – 13 ]. Emerging evidence also implicates a pathogenic role of AGEs in female reproductive disorders [ 14 , 15 ]. Experimental and clinical studies have reported associations between AGEs and ovarian dysfunction, including polycystic ovary syndrome [ 14 , 15 ]. In parallel, oxidative stress has been proposed as a contributor to the pathogenesis of uterine fibroids, based on experimental models and limited clinical observations [ 16 – 20 ]. Given that activation of the AGE–RAGE axis promotes oxidative stress generation [ 4 ], systemic AGE accumulation may plausibly be linked to uterine fibroids. However, direct clinical evidence to show the association between systemic AGE accumulation and uterine fibroids remains scarce. Accordingly, in this retrospective observational study, we investigated whether systemic AGE accumulation assessed by SAF is associated with uterine fibroids in women of reproductive age. In addition, we conducted exploratory analyses to evaluate the potential contribution of oxidative stress to this association. 2. Methods 2.1. Study Design and Study Participants This retrospective observational study included women who visited the Horac Grand Front Osaka Clinic (Osaka, Japan) for infertility treatment between October 2015 and December 2018. Gynecological diseases were diagnosed by Japanese board-certified gynecologists. The exclusion criteria were as follows: (1) age < 18 years; (2) congenital chromosomal or uterine abnormalities; (3) hypothalamic–pituitary–gonadal axis disorders, except for hyperprolactinemia; (4) uncontrolled malignancies or inflammatory diseases; (5) uncontrolled chronic systemic diseases; and (6) cases deemed inappropriate for inclusion by the attending physician. During the study period, SAF assessment was performed in a subset of women undergoing infertility evaluation who consented to SAF measurement as part of the clinic’s lifestyle-related assessment. The present analysis included women who met the eligibility criteria and had available SAF measurements. As shown in Fig. 1 , participants were classified into a uterine fibroids group or a control group without gynecological diseases. Women aged > 40 years were excluded to reduce potential confounding related to hormonal and metabolic changes associated with the menopausal transition. The sample size was determined by the number of eligible women with available SAF measurements during the study period. 2.2. Ethics Statement This study was approved by the Institutional Review Board of Horac Grand Front Osaka Clinic (approval no. 2025-10). The present study was a retrospective analysis of existing clinical data obtained during infertility evaluation between October 2015 and December 2018. No additional procedures were performed for the purpose of this study. In accordance with the Ethical Guidelines for Life Science and Medical Research Involving Human Subjects in Japan, the requirement for written informed consent was waived because this study used anonymized retrospective clinical data and an opt-out consent procedure was applied. All procedures were conducted in accordance with the Declaration of Helsinki and its later amendments. 2.3. Laboratory measurements All participants underwent routine clinical examinations and blood sampling as part of infertility evaluation. Blood samples were obtained during routine clinical practice on days 3–4 of the menstrual cycle, and leftover serum specimens were used for oxidative stress and reproductive hormone measurements. Oxidative stress and antioxidant status were evaluated by measuring serum hydroperoxide levels using diacron-reactive oxygen metabolites (d-ROMs) test and biological antioxidant potential (BAP) test, respectively (Wismerll Company Limited, Bunkyo, Tokyo, Japan), as previously described [ 21 ]. Serum levels of follicle-stimulating hormone (FSH), anti-Müllerian hormone (AMH), prolactin, and dehydroepiandrosterone sulfate (DHEA-S) were measured using an automated clinical chemistry analyzer (COBAS e411; Roche Diagnostics K.K., Tokyo, Japan). 2.4. SAF Measurements Skin accumulation levels of AGEs were evaluated by SAF, measured on the dorsal side of the forearms using a non-invasive autofluorescence reader (TruAge Scanner; Diagnoptics Technologies B.V., Groningen, Netherlands) based on the AGE-Reader™ mu system [ 6 ]. The device illuminates the skin with ultraviolet light (excitation range: 300–400 nm) and detects AGE-specific autofluorescence emission (420–600 nm). SAF was expressed in arbitrary units calculated as the ratio of emitted fluorescent light to excitation light. For comparison with values obtained using the AGE-Reader™ mu, SAF values measured with the TruAge Scanner were divided by 100, as the TruAge Scanner reports values scaled to be 100-fold higher than those of the AGE-Reader™ mu [ 6 ]. 2.5. Statistical Analyses Statistical analyses were performed using JMP version 19.0.3 (SAS Institute Inc., Cary, NC, USA). Continuous variables are presented as medians with interquartile ranges (25th–75th percentiles). Group comparisons were conducted using the Wilcoxon rank-sum test for continuous variables and Fisher’s exact test for categorical variables. Associations between continuous variables were assessed using Spearman’s rank correlation coefficients. Univariable logistic regression analyses were performed to examine associations between individual anthropometric, biochemical, and hormonal variables and the presence of uterine fibroids. Given the limited sample size and the potential for multicollinearity among candidate predictors, variable selection was performed using a generalized linear model with elastic-net regularization. Elastic net regularization was used primarily as a variable-selection approach to reduce potential model instability arising from multicollinearity and the limited sample size. The elastic-net procedure was applied to 2500 bootstrap-resampled datasets, and variables selected in more than 80% of bootstrap samples were subsequently included in multivariable logistic regression models to estimate their independent associations with uterine fibroids. The robustness of multivariable logistic regression estimates was assessed using bootstrap resampling with 2500 iterations. An exploratory mediation analysis was conducted to evaluate whether oxidative stress, assessed by serum d-ROMs, mediated the association between AGE accumulation levels, measured by SAF, and uterine fibroids. A linear regression model was used for the mediator (d-ROMs), and a logistic regression model was used for the outcome (uterine fibroids). Total, direct, and indirect effects were estimated on the probability scale using model-based standardization, and the proportion mediated was calculated as the ratio of the indirect effect to the total effect. The mediation models were adjusted a priori for age, body mass index (BMI), drinking status, SAF, and serum creatinine levels. Smoking status was not included because of the very small number of smokers. The robustness of mediation effect estimates was similarly evaluated using bootstrap resampling with 2500 iterations. All statistical tests were two-sided, and a p value < 0.05 was considered statistically significant. 3. Results 3.1. Clinical Characteristics of the Study Participants The study flow diagram is presented in Fig. 1 . Of the 341 participants enrolled in the original study population, 75 women, including those without gynecological diseases and those with uterine fibroids, were included in the analysis and classified into the control group and the uterine fibroids group, respectively. Comorbid diseases are presented in Supplementary Table S1 . There were no significant differences in comorbidities between the control and uterine fibroid groups. Table 1 summarizes the clinical characteristics of the two groups. Compared with the control group, the uterine fibroids group exhibited significantly higher SAF values and serum d-ROMs and AMH levels, and significantly lower serum FSH levels. Other anthropometric, biochemical, and hormonal parameters were comparable between the two groups. Table 1 Clinical characteristics of the study population Baseline characteristics Control group ( n = 41) Uterine fibroids group ( n = 34) Age (years) 37.0 [33.5–40.0] 38.5 [35.0–39.3] BMI (kg/m 2 ) 19.9 [19.0–21.1] 20.3 [19.3–21.5] Smoking habit, n (%) 1 (2.9) 1 (2.4) Drinking habit, n (%) 9 (22) 4 (12) Oxidative stress and AGE markers SAF (AU) 1.95 [1.74–2.06] 2.19 [1.86–2.35] a Serum d-ROMs (U.CARR) 304 [277–345] 360 [303–398] a Serum BAP (U.CARR) 2250 [2146–2412] 2269 [2178–2408] Hormonal parameters Serum FSH (mIU/mL) 2.5 [1.6–4.5] 1.3 [0.6–2.9] a Serum AMH (ng/mL) 7.3 [6.7–9.2] 8.6 [7.1–10.9] a Serum prolactin (ng/mL) 15.4 [12.1–20.5] 14.0 [11.3–20.5] Serum DHEA-S (µg/dL) 149 [104–214] 132 [101–189] Biochemical parameters Serum AST (IU/L) 16 [ 15 – 21 ] 19 [ 16 – 21 ] Serum ALT (IU/L) 12 [ 10 – 20 ] 14 [ 11 – 17 ] Serum creatinine (mg/dL) 0.6 [0.5–0.6] 0.6 [0.5–0.7] Serum albumin (g/dL) 4.4 [4.3–4.6] 4.4 [4.2–4.7] Serum LDL-C (mg/dL) 111 [95–133] 101 [81–133] Serum HDL-C (mg/dL) 70 [62–78] 72 [58–76] Serum TG (mg/dL) 69 [48–114] 73 [51–96] Data are expressed as median [25th–75th percentile] or n (%). The control group consisted of women without uterine fibroids or other gynecological diseases. a , p < 0.05 vs. control group. BMI: body mass index, SAF: skin autofluorescence, d-ROMs: diacron-reactive oxygen metabolites, BAP: biological antioxidant potential, FSH: follicle-stimulating hormone, AMH: anti-Müllerian hormone, DHEA-S: dehydroepiandrosterone sulfate, AST: aspartate aminotransferase, ALT: alanine aminotransferase, LDL-C: low-density lipoprotein cholesterol, HDL-C: high-density lipoprotein cholesterol, TG: triglycerides. 3.2. Association of SAF, d-ROMs, FSH, and AMH with Uterine Fibroids in Univariable Logistic Regression Analyses Because SAF values and serum levels of d-ROMs, FSH, and AMH differed between the uterine fibroids and control groups, univariable logistic regression analyses were performed to examine their associations with uterine fibroids. As shown in Table 2 , higher SAF values and serum d-ROMs levels were significantly associated with the presence of uterine fibroids, whereas serum FSH and AMH levels were not. Table 2 Univariable logistic regression analysis of anthropometric, biochemical, and hormonal parameters associated with uterine fibroids Variables Odds ratio (95% CI) p- value Age (years) 1.10 [0.95–1.27] 0.22 BMI (kg/m 2 ) 1.10 [0.89–1.37] 0.39 Smoking habit 1.21 [0.073–20] 0.89 Drinking habit 0.47 [0.13–1.7] 0.25 SAF (per 0.1 AU) 1.34 [1.10–1.48] < 0.01 Serum d-ROMs (per 10 U.CARR) 1.17 [1.07–1.30] < 0.01 Serum BAP (per 10 U.CARR) 1.00 [0.98–1.02] 0.85 Serum FSH (mIU/mL) 1.13 [0.98–1.30] 0.10 Serum AMH (ng/mL) 0.92 [0.76–1.11] 0.36 Serum prolactin (ng/mL) 0.96 [0.89–1.03] 0.25 Serum DHEA-S (per 10 µg/dL) 0.98 [0.92–1.04] 0.50 Serum AST (IU/L) 0.97 [0.91–1.04] 0.42 Serum ALT (IU/L) 0.97 [0.93–1.02] 0.27 Serum creatinine (per 0.1 mg/dL) 1.29 [1.00–1.67] 0.07 Serum albumin (g/dL) 0.73 [0.13–4.1] 0.72 Serum LDL-C (mg/dL) 0.99 [0.97–1.01] 0.18 Serum HDL-C (mg/dL) 1.00 [0.97–1.04] 0.90 Serum TG (mg/dL) 1.00 [0.99–1.01] 0.72 Odds ratios represent the change in odds per 1-unit increase in each continuous variable, unless otherwise specified. For SAF, odds ratios are expressed per 0.1 AU; for serum d-ROMs and BAP, per 10 U.CARR; for DHEA-S, per 10 µg/dL; and for serum creatinine, per 0.1 mg/dL. Wide confidence intervals for some variables reflect the limited number of events. CI, confidence intervals. 3.3. Association of SAF and Serum d-ROMs Levels with Uterine Fibroids in Multivariable Logistic Regression Analysis Candidate variables for inclusion in the multivariable logistic regression model were evaluated. As shown in Supplementary Figure S1 , several parameters, including age, BMI, and serum d-ROMs levels, showed modest correlations with SAF (the detailed correlation matrix is presented in Supplementary Tables S2A and S2B). To address potential multicollinearity and identify stable predictors, variable selection was performed using elastic net–regularized logistic regression (Supplementary Table S3). SAF values and serum d-ROMs levels demonstrated the highest selection frequencies, whereas serum low density lipoprotein cholesterol (LDL-C) and FSH levels and drinking status showed moderate selection frequencies. Based on these results, multivariable logistic regression analysis was conducted including the selected variables. As shown in Table 3 , serum d-ROMs levels were independently associated with the presence of uterine fibroids, whereas the association with SAF was attenuated after multivariable adjustment. Table 3 Multivariable logistic regression analysis including variables selected by elastic-net regularization Variables Odds ratio (95% CI) p- value Serum d-ROMs (per 10 U.CARR) 1.16 [1.05–1.31] < 0.01 SAF (per 0.1 AU) 1.02 [0.99–1.04] 0.06 Serum LDL-C (mg/dL) 0.92 [0.96–1.00] 0.06 FSH (mIU/mL) 1.13 [0.96–1.38] 0.15 Drinking habit 0.35 [0.06–1.69] 0.20 Model fit: generalized R ² = 0.23; overall model p -value < 0.001. Odds ratios represent the effect per 1-unit increase in each continuous variable, except for serum d-ROMs (per 10U.CARR) and SAF (per 0.1 AU). The robustness of the multivariable logistic regression estimates was evaluated using bootstrap resampling with 2500 iterations. 3.4. Mediation Analysis for the Association between AGEs and Uterine Fibroids Finally, an exploratory mediation analysis was performed to examine whether oxidative stress, assessed by d-ROMs levels, might explain partly the association between systemic AGE accumulation levels, measured by SAF, and uterine fibroids. The estimated total, direct, and indirect effects are presented in Table 4 , and the mediation model with the relative contributions of each effect is illustrated in Supplementary Figure S2 . The indirect effect via serum d-ROMs explained 46% of the observed association between SAF and uterine fibroids, while the remaining 54% represented the direct effect of SAF estimated in the mediation model, independent of serum d-ROMs. Table 4 Mediation analysis of the association between AGEs and uterine fibroids, with serum d-ROMs as a mediator Effect Estimate (95% CI) Odds ratio (95% CI) Total effect 0.032 [0.032–0.033] 1.03 [1.03–1.03] Direct effect 0.024 [0.023–0.024] 1.02 [1.02–1.03] Indirect effect 0.012 [0.012–0.013] 1.01 [1.01–1.01] Proportion mediated (%) 0.46 [0.42–0.50] Estimates were obtained using generalized linear models adjusted for age, BMI, drinking status, SAF, and serum creatinine levels. Serum d-ROMs was treated as the mediator variable in the mediation analysis. Ninety-five percent confidence intervals (CI) were estimated using 2500 bootstrap resamples. 4. Discussion In this retrospective study of women undergoing infertility evaluation, oxidative stress assessed by serum d-ROMs was higher in women with uterine fibroids and was independently associated with the presence of uterine fibroids. Although systemic AGE accumulation estimated by SAF was also higher in women with uterine fibroids, the association between SAF and uterine fibroids was attenuated after multivariable adjustment. These findings suggest that oxidative stress may represent a more direct biological correlate of uterine fibroids than systemic AGE accumulation in this study population. Exploratory mediation analysis further suggested that oxidative stress statistically explained partly the association between SAF and uterine fibroids. Because of the cross-sectional design, these findings should not be interpreted as evidence of a causal pathway. Overall, the present results highlight oxidative stress as the factor most consistently associated with uterine fibroids in this study population. AGE formation is promoted by metabolic abnormalities and unhealthy lifestyle factors, and once formed, AGEs tend to persist in tissues because of their resistance to degradation and slow clearance [ 4 ]. SAF provides a noninvasive surrogate measure of systemic AGE accumulation [ 5 ]. Reference SAF values in healthy individuals have been reported to be approximately 1.70, 1.80, and 1.90 arbitrary units (AU) at ages 36, 40, and 44 years, respectively [ 6 ]. In the present study, women with uterine fibroids exhibited a median SAF value of 2.19 AU, which was higher than these age-related reference values. Although direct comparisons should be interpreted cautiously because of differences in study populations and designs between them, our present finding is consistent with the possibility that systemic AGE accumulation levels are increased in women of reproductive age with uterine fibroids. Accumulating evidence suggests that oxidative stress plays an important role in the pathogenesis of uterine fibroids through numerous mechanisms involving enhanced cell proliferation, resistance to apoptosis via Akt-mediated pathways, inflammatory signaling, dysregulated autophagy, and growth factor activation [ 16 – 20 ]. Consistent with previous clinical studies reporting elevated circulating oxidative stress markers in women with uterine fibroids [ 22 ], we found that serum d-ROMs levels were higher in women with uterine fibroids than in controls and remained independently associated with uterine fibroids in multivariable logistic regression models. However, exploratory mediation analysis indicated that although approximately half of the association between SAF and uterine fibroids was mediated by oxidative stress, this pathway did not fully explain the observed association. These findings raise the possibility that AGEs may be associated with uterine fibroids through mechanisms beyond oxidative stress alone. A previous study reported increased inflammatory cytokine expression and tissue AGE accumulation in uterine tissues from obese women, suggesting the involvement of AGE-evoked inflammatory reactions [ 23 ]. Because the present study did not include tissue-based analyses, further clinical studies incorporating uterine fibroid tissue samples are warranted to clarify the biological association between AGE accumulation and uterine fibroids. Serum AMH is widely used as a clinical marker of ovarian reserve; however, previous studies have reported inconsistent findings regarding its association with uterine fibroids [ 24 , 25 ]. In the present study, women with uterine fibroids exhibited higher AMH levels and lower FSH levels compared with controls, although neither hormone was significantly associated with uterine fibroids in univariable or multivariable analyses. The present study has several limitations. First, because of its observational design, causal relationships between systemic AGE accumulation and uterine fibroids could not be established, and residual confounding could not be completely excluded. Therefore, the present findings should be interpreted as hypothesis-generating. Second, SAF values are influenced by metabolic status and lifestyle-related factors [ 6 ]; however, detailed information on these factors was not available in this study population. Thus, the upstream determinants contributing to increased SAF values, including diet, remain unclear. Third, systemic AGE accumulation was evaluated by SAF, but AGE levels were not directly measured in uterine or fibroid tissues here. Therefore, the local biological effects of AGEs within fibroid tissue remain unelucidated. Fourth, the study population consisted of women undergoing infertility evaluation. Although this allowed standardized gynecological diagnoses and clinical assessments, the generalizability of the present findings to the broader population of reproductive-age women may be limited. Fifth, SAF measurements were available only for a subset of women undergoing infertility evaluation because the test was optional. Therefore, selection bias cannot be completely excluded. Finally, because the sample size was relatively small, models including multiple variables should be interpreted with caution. Accordingly, the elastic-net and mediation analyses should be considered exploratory. 5. Conclusions The present findings suggest that oxidative stress may be associated with uterine fibroids in women of reproductive age and may represent a potential biological correlate linking AGE accumulation to uterine fibroids. Further prospective and mechanistic studies are warranted to clarify the temporal relationships among AGE accumulation, oxidative stress, and uterine fibroids. Abbreviations AGEs Advanced glycation end products AMH Anti-Müllerian hormone BAP Biological antioxidant potential DHEA-S Dehydroepiandrosterone sulfate d-ROMs Diacron-reactive oxygen metabolites FSH Follicle-stimulating hormone LDL-C low density lipoprotein cholesterol RAGE Receptor for AGEs SAF Skin autofluorescence Declarations Ethics approval and consent to participate The study protocol was approved by the Ethics Review Board of the IVF JAPAN Group (approval no. 2025-10). All procedures were conducted in accordance with the Declaration of Helsinki and its later amendments. This retrospective observational study used existing clinical data obtained during routine infertility treatment, and no additional interventions were performed. In accordance with the Ethical Guidelines for Life Science and Medical Research Involving Human Subjects in Japan, the requirement for written informed consent was waived because of the retrospective nature of the study, and an opt-out consent procedure was applied. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions imposed by the institutional review board. De-identified data may be made available from the corresponding author upon reasonable request and subject to appropriate ethical approval and data use agreements. Competing interests The authors declare the following competing interest. Y. Mori. received financial support from Boehringer Ingelheim GmbH (Ingelheim am Rhein, Germany) and Ono Pharmaceutical Co., Ltd. (Osaka, Japan). F. I. is an employee of partner.co worldwide incorporated, which had no relation to the present study. S. Y. has received lecture fees from Bayer Yakuhin, Ltd., Kowa Company, Ltd., and Novo Nordisk Pharma, Ltd. The other authors declare no competing interests. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Authors' contributions T. N.: Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing—review and editing, and visualization. Y. Mori: software, validation, formal analysis, data curation, writing—original draft preparation, and visualization. K. O.: investigation and writing—review and editing. F. I.: investigation and writing—review and editing. S.Y.: methodology, writing—review and editing, and supervision Y. 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Maghraby N, El Noweihi AM, El-Melegy NT, Mostafa NAM, Abbas AM, El-Deek HEM, et al. Increased expression of fibroblast activation protein is associated with autophagy dysregulation and oxidative stress in obese women with uterine fibroids. Reprod Sci. 2022;29:448–59. Zhang M, Liu C, Yuan XQ, Cui FP, Miao Y, Yao W, et al. Oxidatively generated DNA damage mediates the associations of exposure to phthalates with uterine fibroids and endometriosis: Findings from TREE cohort. Free Radic Biol Med. 2023;205:69–76. Cesarone MR, Belcaro G, Carratelli M, Cornelli U, De Sanctis MT, Incandela L, et al. A simple test to monitor oxidative stress. Int Angiol. 1999;18:127–30. Santulli P, Borghese B, Lemaréchal H, Leconte M, Millischer AE, Batteux F, et al. Increased serum oxidative stress markers in women with uterine leiomyoma. PLoS ONE. 2013;8:e72069. Antoniotti GS, Coughlan M, Salamonsen LA, Evans J. Obesity associated advanced glycation end products within the human uterine cavity adversely impact endometrial function and embryo implantation competence. Hum Reprod. 2018;33:654–65. Bernardi LA, Waldo A, Berrocal VJ, Wise LA, Marsh EE. Association between uterine fibroids and antimüllerian hormone concentrations among African American women. Fertil Steril. 2022;117:832–40. Moini A, Kalhor M, Jahanian Sadatmahalleh S, Niknejadi M, Nasiri M, Yahyaei A, et al. Evaluation of the relationship between ovarian reserve with congenital anomalies and intramural uterine leiomyoma among infertile women: a cross-sectional study. J Ovarian Res. 2023;16:68. Additional Declarations Competing interest reported. The authors declare the following competing interest. Y. Mori. received financial support from Boehringer Ingelheim GmbH (Ingelheim am Rhein, Germany) and Ono Pharmaceutical Co., Ltd. (Osaka, Japan). F. I. is an employee of partner.co worldwide incorporated, which had no relation to the present study. S. Y. has received lecture fees from Bayer Yakuhin, Ltd., Kowa Company, Ltd., and Novo Nordisk Pharma, Ltd. The other authors declare no competing interests. Supplementary Files SupplementaryFigsMar13.docx SupplementaryTablesMar13.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 17 Apr, 2026 Editor invited by journal 26 Mar, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 24 Mar, 2026 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-9217861","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628441113,"identity":"66090c89-02f0-4787-abbe-197cc8cb51f2","order_by":0,"name":"Takuji Nishihara","email":"","orcid":"","institution":"IVF Namba Clinic","correspondingAuthor":false,"prefix":"","firstName":"Takuji","middleName":"","lastName":"Nishihara","suffix":""},{"id":628441114,"identity":"7cc87715-e9f0-41d0-9619-825e8222ad67","order_by":1,"name":"Yusaku Mori","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYNACAxsgkcDAjCTERkhLGslaGA5jaMFj/gHuxMcVBeej+dkTmD8XVByWZ5BIYPzwg4EvD7cW3s2GZwxu587secAmPePMYcMGiQRmyR4GtmKcWu6/3SbZANSy4UYCGzNv223G/TcSGKSBfklswG0LSMu5XKBK5s9ALfYgW34ToeVA7gYJoOFALYlALWx4bZEE+aXBIDl3xpmHbdI8Z/4nN/A8bLPsMcDtF74DvBsfNvyxy+1vTz78macizbaBPfnwjR8Vx3CGGBJgbEBiGBxLIEILKqghXcsoGAWjYBQMVwAAXEJUMg5DLeYAAAAASUVORK5CYII=","orcid":"","institution":"Showa University","correspondingAuthor":true,"prefix":"","firstName":"Yusaku","middleName":"","lastName":"Mori","suffix":""},{"id":628441115,"identity":"2eeb8f59-8547-4caa-94b1-4fc56c8e67ef","order_by":2,"name":"Kuniaki Ota","email":"","orcid":"","institution":"Kawasaki Medical School","correspondingAuthor":false,"prefix":"","firstName":"Kuniaki","middleName":"","lastName":"Ota","suffix":""},{"id":628441116,"identity":"89c1b897-8ec7-481a-832b-d257767fb16b","order_by":3,"name":"Fumiyuki Isami","email":"","orcid":"","institution":"Partner.co worldwide incorporated","correspondingAuthor":false,"prefix":"","firstName":"Fumiyuki","middleName":"","lastName":"Isami","suffix":""},{"id":628441117,"identity":"080fdca8-2719-4f48-9429-e45ebea9e5cb","order_by":4,"name":"Sho-Ichi Yamagishi","email":"","orcid":"","institution":"Showa University","correspondingAuthor":false,"prefix":"","firstName":"Sho-Ichi","middleName":"","lastName":"Yamagishi","suffix":""},{"id":628441118,"identity":"e070d7b4-6619-4ab5-b5ba-7049f5768c24","order_by":5,"name":"Yoshiharu Nakaoka","email":"","orcid":"","institution":"IVF Namba Clinic","correspondingAuthor":false,"prefix":"","firstName":"Yoshiharu","middleName":"","lastName":"Nakaoka","suffix":""},{"id":628441119,"identity":"165accbc-cee8-40ca-b8c7-f244ee03fe50","order_by":6,"name":"Yoshiharu Morimoto","email":"","orcid":"","institution":"HORAC IVF Grand Front","correspondingAuthor":false,"prefix":"","firstName":"Yoshiharu","middleName":"","lastName":"Morimoto","suffix":""}],"badges":[],"createdAt":"2026-03-25 04:08:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9217861/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9217861/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107708113,"identity":"bf09fc83-72c0-490a-b2e3-865f878aae76","added_by":"auto","created_at":"2026-04-24 09:21:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":571769,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy flow diagram.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlow diagram of participant selection and exclusion criteria. Women aged \u0026gt; 40 years were excluded to minimize potential confounding effects of perimenopausal hormonal changes.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-9217861/v1/5181357c763aefc953b90d16.png"},{"id":108490807,"identity":"0bd7f4cb-4660-4bc3-a595-c1b3df1b4d74","added_by":"auto","created_at":"2026-05-05 09:48:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1540656,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9217861/v1/50314684-b676-4fd7-9ee8-6ef060d3e9ad.pdf"},{"id":107701037,"identity":"ec4de57d-9422-476a-ad51-8751632386dc","added_by":"auto","created_at":"2026-04-24 08:07:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":115247,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigsMar13.docx","url":"https://assets-eu.researchsquare.com/files/rs-9217861/v1/898ccea408bd21e29ab7549c.docx"},{"id":107701039,"identity":"65cf44c3-c228-4b2f-ae84-3e89335490d8","added_by":"auto","created_at":"2026-04-24 08:07:06","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":29756,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesMar13.docx","url":"https://assets-eu.researchsquare.com/files/rs-9217861/v1/c1bebc58eddf1fe86015070c.docx"}],"financialInterests":"Competing interest reported. The authors declare the following competing interest. Y. Mori. received financial support from Boehringer Ingelheim GmbH (Ingelheim am Rhein, Germany) and Ono Pharmaceutical Co., Ltd. (Osaka, Japan). F. I. is an employee of partner.co worldwide incorporated, which had no relation to the present study. S. Y. has received lecture fees from Bayer Yakuhin, Ltd., Kowa Company, Ltd., and Novo Nordisk Pharma, Ltd. The other authors declare no competing interests.","formattedTitle":"Association of Oxidative Stress and Advanced Glycation End Products with Uterine Fibroids in Women of Reproductive Age: a Retrospective Observational Study","fulltext":[{"header":"1. Background","content":"\u003cp\u003eUterine fibroids are common benign uterine tumors in women of reproductive age and represent a major cause of pelvic pain, abnormal uterine bleeding, infertility, and impaired quality of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Epidemiological studies have reported that metabolic derangements and unhealthy lifestyle habits, including obesity, alcohol consumption, and smoking, are associated with uterine fibroids [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, despite their substantial clinical burden, the biological mechanisms linking systemic metabolic disturbances and lifestyle factors to fibroid development remain incompletely understood.\u003c/p\u003e \u003cp\u003eAdvanced glycation end products (AGEs) are heterogeneous macromolecular adducts formed through nonenzymatic reactions between monosaccharides and amino groups of proteins, lipids, and nucleic acids [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Endogenous AGE formation is accelerated under conditions such as diabetes, obesity, and aging, while dietary intake represents an important source of exogenous AGEs in humans [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Accumulating evidence suggests that AGEs activate inflammatory and oxidative pathways in multiple tissues via interaction with the receptor for AGEs (RAGE), thereby contributing to the pathogenesis of various chronic noncommunicable diseases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBecause several AGE species exhibit autofluorescence, systemic AGE accumulation can be noninvasively assessed using skin autofluorescence (SAF) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. SAF has been shown to correlate with tissue accumulation of both fluorescent and nonfluorescent AGEs, and skin AGE content has been reported to account for approximately 76% of the variance in SAF, supporting its use as a surrogate biomarker of cumulative metabolic stress- and lifestyle-related AGE accumulation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Previous studies have demonstrated associations between elevated SAF and adverse clinical outcomes, including cardiovascular disease, cancer, and all-cause mortality, in both diabetic and non-diabetic populations [\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11 CR12\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEmerging evidence also implicates a pathogenic role of AGEs in female reproductive disorders [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Experimental and clinical studies have reported associations between AGEs and ovarian dysfunction, including polycystic ovary syndrome [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In parallel, oxidative stress has been proposed as a contributor to the pathogenesis of uterine fibroids, based on experimental models and limited clinical observations [\u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Given that activation of the AGE\u0026ndash;RAGE axis promotes oxidative stress generation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], systemic AGE accumulation may plausibly be linked to uterine fibroids. However, direct clinical evidence to show the association between systemic AGE accumulation and uterine fibroids remains scarce. Accordingly, in this retrospective observational study, we investigated whether systemic AGE accumulation assessed by SAF is associated with uterine fibroids in women of reproductive age. In addition, we conducted exploratory analyses to evaluate the potential contribution of oxidative stress to this association.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design and Study Participants\u003c/h2\u003e \u003cp\u003eThis retrospective observational study included women who visited the Horac Grand Front Osaka Clinic (Osaka, Japan) for infertility treatment between October 2015 and December 2018. Gynecological diseases were diagnosed by Japanese board-certified gynecologists. The exclusion criteria were as follows: (1) age\u0026thinsp;\u0026lt;\u0026thinsp;18 years; (2) congenital chromosomal or uterine abnormalities; (3) hypothalamic\u0026ndash;pituitary\u0026ndash;gonadal axis disorders, except for hyperprolactinemia; (4) uncontrolled malignancies or inflammatory diseases; (5) uncontrolled chronic systemic diseases; and (6) cases deemed inappropriate for inclusion by the attending physician.\u003c/p\u003e \u003cp\u003eDuring the study period, SAF assessment was performed in a subset of women undergoing infertility evaluation who consented to SAF measurement as part of the clinic\u0026rsquo;s lifestyle-related assessment. The present analysis included women who met the eligibility criteria and had available SAF measurements. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, participants were classified into a uterine fibroids group or a control group without gynecological diseases. Women aged\u0026thinsp;\u0026gt;\u0026thinsp;40 years were excluded to reduce potential confounding related to hormonal and metabolic changes associated with the menopausal transition. The sample size was determined by the number of eligible women with available SAF measurements during the study period.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Ethics Statement\u003c/h2\u003e \u003cp\u003e This study was approved by the Institutional Review Board of Horac Grand Front Osaka Clinic (approval no. 2025-10). The present study was a retrospective analysis of existing clinical data obtained during infertility evaluation between October 2015 and December 2018. No additional procedures were performed for the purpose of this study. In accordance with the Ethical Guidelines for Life Science and Medical Research Involving Human Subjects in Japan, the requirement for written informed consent was waived because this study used anonymized retrospective clinical data and an opt-out consent procedure was applied. All procedures were conducted in accordance with the Declaration of Helsinki and its later amendments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Laboratory measurements\u003c/h2\u003e \u003cp\u003eAll participants underwent routine clinical examinations and blood sampling as part of infertility evaluation. Blood samples were obtained during routine clinical practice on days 3\u0026ndash;4 of the menstrual cycle, and leftover serum specimens were used for oxidative stress and reproductive hormone measurements. Oxidative stress and antioxidant status were evaluated by measuring serum hydroperoxide levels using diacron-reactive oxygen metabolites (d-ROMs) test and biological antioxidant potential (BAP) test, respectively (Wismerll Company Limited, Bunkyo, Tokyo, Japan), as previously described [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Serum levels of follicle-stimulating hormone (FSH), anti-M\u0026uuml;llerian hormone (AMH), prolactin, and dehydroepiandrosterone sulfate (DHEA-S) were measured using an automated clinical chemistry analyzer (COBAS e411; Roche Diagnostics K.K., Tokyo, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. SAF Measurements\u003c/h2\u003e \u003cp\u003eSkin accumulation levels of AGEs were evaluated by SAF, measured on the dorsal side of the forearms using a non-invasive autofluorescence reader (TruAge Scanner; Diagnoptics Technologies B.V., Groningen, Netherlands) based on the AGE-Reader\u0026trade; mu system [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The device illuminates the skin with ultraviolet light (excitation range: 300\u0026ndash;400 nm) and detects AGE-specific autofluorescence emission (420\u0026ndash;600 nm). SAF was expressed in arbitrary units calculated as the ratio of emitted fluorescent light to excitation light. For comparison with values obtained using the AGE-Reader\u0026trade; mu, SAF values measured with the TruAge Scanner were divided by 100, as the TruAge Scanner reports values scaled to be 100-fold higher than those of the AGE-Reader\u0026trade; mu [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical Analyses\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using JMP version 19.0.3 (SAS Institute Inc., Cary, NC, USA). Continuous variables are presented as medians with interquartile ranges (25th\u0026ndash;75th percentiles). Group comparisons were conducted using the Wilcoxon rank-sum test for continuous variables and Fisher\u0026rsquo;s exact test for categorical variables. Associations between continuous variables were assessed using Spearman\u0026rsquo;s rank correlation coefficients. Univariable logistic regression analyses were performed to examine associations between individual anthropometric, biochemical, and hormonal variables and the presence of uterine fibroids.\u003c/p\u003e \u003cp\u003eGiven the limited sample size and the potential for multicollinearity among candidate predictors, variable selection was performed using a generalized linear model with elastic-net regularization. Elastic net regularization was used primarily as a variable-selection approach to reduce potential model instability arising from multicollinearity and the limited sample size. The elastic-net procedure was applied to 2500 bootstrap-resampled datasets, and variables selected in more than 80% of bootstrap samples were subsequently included in multivariable logistic regression models to estimate their independent associations with uterine fibroids. The robustness of multivariable logistic regression estimates was assessed using bootstrap resampling with 2500 iterations.\u003c/p\u003e \u003cp\u003eAn exploratory mediation analysis was conducted to evaluate whether oxidative stress, assessed by serum d-ROMs, mediated the association between AGE accumulation levels, measured by SAF, and uterine fibroids. A linear regression model was used for the mediator (d-ROMs), and a logistic regression model was used for the outcome (uterine fibroids). Total, direct, and indirect effects were estimated on the probability scale using model-based standardization, and the proportion mediated was calculated as the ratio of the indirect effect to the total effect. The mediation models were adjusted a priori for age, body mass index (BMI), drinking status, SAF, and serum creatinine levels. Smoking status was not included because of the very small number of smokers. The robustness of mediation effect estimates was similarly evaluated using bootstrap resampling with 2500 iterations. All statistical tests were two-sided, and a \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Clinical Characteristics of the Study Participants\u003c/h2\u003e \u003cp\u003eThe study flow diagram is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Of the 341 participants enrolled in the original study population, 75 women, including those without gynecological diseases and those with uterine fibroids, were included in the analysis and classified into the control group and the uterine fibroids group, respectively. Comorbid diseases are presented in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. There were no significant differences in comorbidities between the control and uterine fibroid groups. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the clinical characteristics of the two groups. Compared with the control group, the uterine fibroids group exhibited significantly higher SAF values and serum d-ROMs and AMH levels, and significantly lower serum FSH levels. Other anthropometric, biochemical, and hormonal parameters were comparable between the two groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;41)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUterine fibroids group\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.0 [33.5\u0026ndash;40.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.5 [35.0\u0026ndash;39.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.9 [19.0\u0026ndash;21.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.3 [19.3\u0026ndash;21.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking habit, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking habit, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxidative stress and AGE markers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAF (AU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.95 [1.74\u0026ndash;2.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.19 [1.86\u0026ndash;2.35] \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum d-ROMs (U.CARR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e304 [277\u0026ndash;345]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e360 [303\u0026ndash;398] \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum BAP (U.CARR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2250 [2146\u0026ndash;2412]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2269 [2178\u0026ndash;2408]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHormonal parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum FSH (mIU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5 [1.6\u0026ndash;4.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3 [0.6\u0026ndash;2.9] \u003csup\u003ea\u003c/sup\u003e\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3 [6.7\u0026ndash;9.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6 [7.1\u0026ndash;10.9] \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum prolactin (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.4 [12.1\u0026ndash;20.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.0 [11.3\u0026ndash;20.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum DHEA-S (\u0026micro;g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149 [104\u0026ndash;214]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132 [101\u0026ndash;189]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiochemical parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum AST (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 [\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 [\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ALT (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 [\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 [\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6 [0.5\u0026ndash;0.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 [0.5\u0026ndash;0.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum albumin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4 [4.3\u0026ndash;4.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.4 [4.2\u0026ndash;4.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum LDL-C (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 [95\u0026ndash;133]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 [81\u0026ndash;133]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum HDL-C (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 [62\u0026ndash;78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 [58\u0026ndash;76]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum TG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 [48\u0026ndash;114]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 [51\u0026ndash;96]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eData are expressed as median [25th\u0026ndash;75th percentile] or \u003cem\u003en\u003c/em\u003e (%). The control group consisted of women without uterine fibroids or other gynecological diseases. \u003csup\u003ea\u003c/sup\u003e, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. control group. BMI: body mass index, SAF: skin autofluorescence, d-ROMs: diacron-reactive oxygen metabolites, BAP: biological antioxidant potential, FSH: follicle-stimulating hormone, AMH: anti-M\u0026uuml;llerian hormone, DHEA-S: dehydroepiandrosterone sulfate, AST: aspartate aminotransferase, ALT: alanine aminotransferase, LDL-C: low-density lipoprotein cholesterol, HDL-C: high-density lipoprotein cholesterol, TG: triglycerides.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Association of SAF, d-ROMs, FSH, and AMH with Uterine Fibroids in Univariable Logistic Regression Analyses\u003c/h2\u003e \u003cp\u003eBecause SAF values and serum levels of d-ROMs, FSH, and AMH differed between the uterine fibroids and control groups, univariable logistic regression analyses were performed to examine their associations with uterine fibroids. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, higher SAF values and serum d-ROMs levels were significantly associated with the presence of uterine fibroids, whereas serum FSH and AMH levels were not.\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\u003eUnivariable logistic regression analysis of anthropometric, biochemical, and hormonal parameters associated with uterine fibroids\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.10 [0.95\u0026ndash;1.27]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.10 [0.89\u0026ndash;1.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking habit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.21 [0.073\u0026ndash;20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking habit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.47 [0.13\u0026ndash;1.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAF (per 0.1 AU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.34 [1.10\u0026ndash;1.48]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum d-ROMs (per 10 U.CARR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.17 [1.07\u0026ndash;1.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum BAP (per 10 U.CARR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [0.98\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum FSH (mIU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.13 [0.98\u0026ndash;1.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.10\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=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92 [0.76\u0026ndash;1.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum prolactin (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96 [0.89\u0026ndash;1.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum DHEA-S (per 10 \u0026micro;g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.98 [0.92\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum AST (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97 [0.91\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ALT (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97 [0.93\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine (per 0.1 mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.29 [1.00\u0026ndash;1.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum albumin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.73 [0.13\u0026ndash;4.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum LDL-C (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99 [0.97\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum HDL-C (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [0.97\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum TG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [0.99\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eOdds ratios represent the change in odds per 1-unit increase in each continuous variable, unless otherwise specified. For SAF, odds ratios are expressed per 0.1 AU; for serum d-ROMs and BAP, per 10 U.CARR; for DHEA-S, per 10 \u0026micro;g/dL; and for serum creatinine, per 0.1 mg/dL. Wide confidence intervals for some variables reflect the limited number of events. CI, confidence intervals.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Association of SAF and Serum d-ROMs Levels with Uterine Fibroids in Multivariable Logistic Regression Analysis\u003c/h2\u003e \u003cp\u003eCandidate variables for inclusion in the multivariable logistic regression model were evaluated. As shown in Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, several parameters, including age, BMI, and serum d-ROMs levels, showed modest correlations with SAF (the detailed correlation matrix is presented in Supplementary Tables S2A and S2B). To address potential multicollinearity and identify stable predictors, variable selection was performed using elastic net\u0026ndash;regularized logistic regression (Supplementary Table S3). SAF values and serum d-ROMs levels demonstrated the highest selection frequencies, whereas serum low density lipoprotein cholesterol (LDL-C) and FSH levels and drinking status showed moderate selection frequencies. Based on these results, multivariable logistic regression analysis was conducted including the selected variables. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, serum d-ROMs levels were independently associated with the presence of uterine fibroids, whereas the association with SAF was attenuated after multivariable adjustment.\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\u003eMultivariable logistic regression analysis including variables selected by elastic-net regularization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum d-ROMs (per 10 U.CARR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.16 [1.05\u0026ndash;1.31]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAF (per 0.1 AU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02 [0.99\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum LDL-C (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92 [0.96\u0026ndash;1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFSH (mIU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.13 [0.96\u0026ndash;1.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking habit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.35 [0.06\u0026ndash;1.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eModel fit: generalized \u003cem\u003eR\u003c/em\u003e\u0026sup2; = 0.23; overall model \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Odds ratios represent the effect per 1-unit increase in each continuous variable, except for serum d-ROMs (per 10U.CARR) and SAF (per 0.1 AU). The robustness of the multivariable logistic regression estimates was evaluated using bootstrap resampling with 2500 iterations.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Mediation Analysis for the Association between AGEs and Uterine Fibroids\u003c/h2\u003e \u003cp\u003eFinally, an exploratory mediation analysis was performed to examine whether oxidative stress, assessed by d-ROMs levels, might explain partly the association between systemic AGE accumulation levels, measured by SAF, and uterine fibroids. The estimated total, direct, and indirect effects are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, and the mediation model with the relative contributions of each effect is illustrated in Supplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. The indirect effect via serum d-ROMs explained 46% of the observed association between SAF and uterine fibroids, while the remaining 54% represented the direct effect of SAF estimated in the mediation model, independent of serum d-ROMs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMediation analysis of the association between AGEs and uterine fibroids, with serum d-ROMs as a mediator\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.032 [0.032\u0026ndash;0.033]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.03 [1.03\u0026ndash;1.03]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.024 [0.023\u0026ndash;0.024]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.02 [1.02\u0026ndash;1.03]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.012 [0.012\u0026ndash;0.013]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01 [1.01\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProportion mediated (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.46 [0.42\u0026ndash;0.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eEstimates were obtained using generalized linear models adjusted for age, BMI, drinking status, SAF, and serum creatinine levels. Serum d-ROMs was treated as the mediator variable in the mediation analysis. Ninety-five percent confidence intervals (CI) were estimated using 2500 bootstrap resamples.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this retrospective study of women undergoing infertility evaluation, oxidative stress assessed by serum d-ROMs was higher in women with uterine fibroids and was independently associated with the presence of uterine fibroids. Although systemic AGE accumulation estimated by SAF was also higher in women with uterine fibroids, the association between SAF and uterine fibroids was attenuated after multivariable adjustment. These findings suggest that oxidative stress may represent a more direct biological correlate of uterine fibroids than systemic AGE accumulation in this study population. Exploratory mediation analysis further suggested that oxidative stress statistically explained partly the association between SAF and uterine fibroids. Because of the cross-sectional design, these findings should not be interpreted as evidence of a causal pathway. Overall, the present results highlight oxidative stress as the factor most consistently associated with uterine fibroids in this study population.\u003c/p\u003e \u003cp\u003eAGE formation is promoted by metabolic abnormalities and unhealthy lifestyle factors, and once formed, AGEs tend to persist in tissues because of their resistance to degradation and slow clearance [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. SAF provides a noninvasive surrogate measure of systemic AGE accumulation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Reference SAF values in healthy individuals have been reported to be approximately 1.70, 1.80, and 1.90 arbitrary units (AU) at ages 36, 40, and 44 years, respectively [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the present study, women with uterine fibroids exhibited a median SAF value of 2.19 AU, which was higher than these age-related reference values. Although direct comparisons should be interpreted cautiously because of differences in study populations and designs between them, our present finding is consistent with the possibility that systemic AGE accumulation levels are increased in women of reproductive age with uterine fibroids.\u003c/p\u003e \u003cp\u003eAccumulating evidence suggests that oxidative stress plays an important role in the pathogenesis of uterine fibroids through numerous mechanisms involving enhanced cell proliferation, resistance to apoptosis via Akt-mediated pathways, inflammatory signaling, dysregulated autophagy, and growth factor activation [\u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Consistent with previous clinical studies reporting elevated circulating oxidative stress markers in women with uterine fibroids [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], we found that serum d-ROMs levels were higher in women with uterine fibroids than in controls and remained independently associated with uterine fibroids in multivariable logistic regression models. However, exploratory mediation analysis indicated that although approximately half of the association between SAF and uterine fibroids was mediated by oxidative stress, this pathway did not fully explain the observed association. These findings raise the possibility that AGEs may be associated with uterine fibroids through mechanisms beyond oxidative stress alone. A previous study reported increased inflammatory cytokine expression and tissue AGE accumulation in uterine tissues from obese women, suggesting the involvement of AGE-evoked inflammatory reactions [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Because the present study did not include tissue-based analyses, further clinical studies incorporating uterine fibroid tissue samples are warranted to clarify the biological association between AGE accumulation and uterine fibroids.\u003c/p\u003e \u003cp\u003eSerum AMH is widely used as a clinical marker of ovarian reserve; however, previous studies have reported inconsistent findings regarding its association with uterine fibroids [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In the present study, women with uterine fibroids exhibited higher AMH levels and lower FSH levels compared with controls, although neither hormone was significantly associated with uterine fibroids in univariable or multivariable analyses.\u003c/p\u003e \u003cp\u003eThe present study has several limitations. First, because of its observational design, causal relationships between systemic AGE accumulation and uterine fibroids could not be established, and residual confounding could not be completely excluded. Therefore, the present findings should be interpreted as hypothesis-generating. Second, SAF values are influenced by metabolic status and lifestyle-related factors [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]; however, detailed information on these factors was not available in this study population. Thus, the upstream determinants contributing to increased SAF values, including diet, remain unclear. Third, systemic AGE accumulation was evaluated by SAF, but AGE levels were not directly measured in uterine or fibroid tissues here. Therefore, the local biological effects of AGEs within fibroid tissue remain unelucidated. Fourth, the study population consisted of women undergoing infertility evaluation. Although this allowed standardized gynecological diagnoses and clinical assessments, the generalizability of the present findings to the broader population of reproductive-age women may be limited. Fifth, SAF measurements were available only for a subset of women undergoing infertility evaluation because the test was optional. Therefore, selection bias cannot be completely excluded. Finally, because the sample size was relatively small, models including multiple variables should be interpreted with caution. Accordingly, the elastic-net and mediation analyses should be considered exploratory.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe present findings suggest that oxidative stress may be associated with uterine fibroids in women of reproductive age and may represent a potential biological correlate linking AGE accumulation to uterine fibroids. Further prospective and mechanistic studies are warranted to clarify the temporal relationships among AGE accumulation, oxidative stress, and uterine fibroids.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAGEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdvanced glycation end products\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAMH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnti-M\u0026uuml;llerian hormone\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBiological antioxidant potential\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDHEA-S\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDehydroepiandrosterone sulfate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ed-ROMs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiacron-reactive oxygen metabolites\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFSH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFollicle-stimulating hormone\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLDL-C\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elow density lipoprotein cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRAGE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceptor for AGEs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSkin autofluorescence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Review Board of the IVF JAPAN Group (approval no. 2025-10). All procedures were conducted in accordance with the Declaration of Helsinki and its later amendments.\u003c/p\u003e\n\u003cp\u003eThis retrospective observational study used existing clinical data obtained during routine infertility treatment, and no additional interventions were performed. In accordance with the Ethical Guidelines for Life Science and Medical Research Involving Human Subjects in Japan, the requirement for written informed consent was waived because of the retrospective nature of the study, and an opt-out consent procedure was applied.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions imposed by the institutional review board. De-identified data may be made available from the corresponding author upon reasonable request and subject to appropriate ethical approval and data use agreements.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare the following competing interest. Y. Mori. received financial support from Boehringer Ingelheim GmbH (Ingelheim am Rhein, Germany) and Ono Pharmaceutical Co., Ltd. (Osaka, Japan). F. I. is an employee of partner.co worldwide incorporated, which had no relation to the present study. S. Y. has received lecture fees from Bayer Yakuhin, Ltd., Kowa Company, Ltd., and Novo Nordisk Pharma, Ltd. The other authors declare no competing interests.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eT. N.: Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing\u0026mdash;review and editing, and visualization.\u003c/p\u003e\n\u003cp\u003eY. Mori: software, validation, formal analysis, data curation, writing\u0026mdash;original draft preparation, and visualization.\u003c/p\u003e\n\u003cp\u003eK. O.: investigation and writing\u0026mdash;review and editing.\u003c/p\u003e\n\u003cp\u003eF. I.: investigation and writing\u0026mdash;review and editing.\u003c/p\u003e\n\u003cp\u003eS.Y.: methodology, writing\u0026mdash;review and editing, and supervision\u003c/p\u003e\n\u003cp\u003eY. N.: writing\u0026mdash;review and editing, and supervision.\u003c/p\u003e\n\u003cp\u003eY. Morimoto: conceptualization, methodology, resources, writing\u0026mdash;review and editing, supervision, project administration, and funding acquisition.\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone. \u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCarson SA, Kallen AN. Diagnosis and management of infertility. JAMA. 2021;326:65\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePavone D, Clemenza S, Sorbi F, Fambrini M, Petraglia F. Epidemiology and Risk Factors of Uterine Fibroids. Best Pract Res Clin Obstet Gynaecol. 2018;46:3\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSparic R, Mirkovic L, Malvasi A, Tinelli A. Epidemiology of Uterine Myomas: A Review. Int J Fertil Steril. 2016;9:424\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamagishi SI, Matsui T. Pathologic role of dietary advanced glycation end products in cardiometabolic disorders, and therapeutic intervention. Nutrition. 2016;32:157\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeerwaldt R, Graaff R, Oomen PHN, Links TP, Jager JJ, Alderson NL, et al. Simple non-invasive assessment of advanced glycation endproduct accumulation. Diabetologia. 2004;47:1324\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsami F, West BJ, Nakajima S, Yamagishi SI. Association of advanced glycation end products, evaluated by skin autofluorescence, with lifestyle habits in a general Japanese population. J Int Med Res. 2018;46:1043\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen J, Arshi B, Waqas K, Lu T, Bos D, Ikram MA, et al. Advanced glycation end products measured by skin autofluorescence and subclinical cardiovascular disease: The Rotterdam study. Cardiovasc Diabetol. 2023;22:326.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRigalleau V, Pucheux Y, Couffinhal T, Tessier FJ, Howsam M, Rubin S, et al. Skin autofluorescence of advanced glycation end-products, glycemic memory, and diabetes complications. Diabetes Metab. 2024;51:101600.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFujino Y, Attizzani GF, Tahara S, Wang W, Takagi K, Naganuma T, et al. Association of skin autofluorescence with plaque vulnerability evaluated by optical coherence tomography in patients with cardiovascular disease. Atherosclerosis. 2018;274:47\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagano M, Fukami K, Yamagishi S, Sakai K, Kaida Y, Matsumoto T, et al. Tissue level of advanced glycation end products is an independent determinant of high-sensitivity C-reactive protein levels in haemodialysis patients. Nephrol (Carlton). 2011;16:299\u0026ndash;303.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamagishi SI, Fukami K, Matsui T. Evaluation of tissue accumulation levels of advanced glycation end products by skin autofluorescence: A novel marker of vascular complications in high-risk patients for cardiovascular disease. Int J Cardiol. 2015;185:263\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Waateringe RP, Fokkens BT, Slagter SN, van der Klauw MM, van Vliet- Ostaptchouk JV, Graaff R, et al. Skin autofluorescence predicts incident type 2 diabetes, cardiovascular disease and mortality in the general population. Diabetologia. 2019;62:269\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaqas K, Chen J, Trajanoska K, Ikram MA, Uitterlinden AG, Rivadeneira F, et al. Skin autofluorescence, a noninvasive biomarker for advanced glycation end-products, is associated with sarcopenia. J Clin Endocrinol Metab. 2022;107:e793\u0026ndash;803.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRutkowska A, Diamanti-Kandarakis E. Do advanced glycation end products (ages) contribute to the comorbidities of polycystic ovary syndrome (PCOS)? Curr Pharm Des. 2016;22:5558\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThornton K, Merhi Z, Jindal S, Goldsammler M, Charron MJ, Buyuk E. Dietary advanced glycation end products (ages) could alter ovarian function in mice. Mol Cell Endocrinol. 2020;510:110826.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVidimar V, Chakravarti D, Bulun SE, Yin P, Nowak R, Wei JJ, et al. The AKT/BCL-2 axis mediates survival of uterine leiomyoma in a novel 3D spheroid model. Endocrinology. 2018;159:1453\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu X, Kim JJ, Li Y, Xie J, Shao C, Wei JJ. Oxidative stress-induced mirnas modulate AKT signaling and promote cellular senescence in uterine leiomyoma. J Mol Med. 2018;96:1095\u0026ndash;106.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Chen H, Zhang H, Lin Z, Song L, Zhao C. Identification of oxidative stress-related biomarkers in uterine leiomyoma: A transcriptome-combined mendelian randomization analysis. Front Endocrinol. 2024;15:1373011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaghraby N, El Noweihi AM, El-Melegy NT, Mostafa NAM, Abbas AM, El-Deek HEM, et al. Increased expression of fibroblast activation protein is associated with autophagy dysregulation and oxidative stress in obese women with uterine fibroids. Reprod Sci. 2022;29:448\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang M, Liu C, Yuan XQ, Cui FP, Miao Y, Yao W, et al. Oxidatively generated DNA damage mediates the associations of exposure to phthalates with uterine fibroids and endometriosis: Findings from TREE cohort. Free Radic Biol Med. 2023;205:69\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCesarone MR, Belcaro G, Carratelli M, Cornelli U, De Sanctis MT, Incandela L, et al. A simple test to monitor oxidative stress. Int Angiol. 1999;18:127\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantulli P, Borghese B, Lemar\u0026eacute;chal H, Leconte M, Millischer AE, Batteux F, et al. Increased serum oxidative stress markers in women with uterine leiomyoma. PLoS ONE. 2013;8:e72069.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntoniotti GS, Coughlan M, Salamonsen LA, Evans J. Obesity associated advanced glycation end products within the human uterine cavity adversely impact endometrial function and embryo implantation competence. Hum Reprod. 2018;33:654\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernardi LA, Waldo A, Berrocal VJ, Wise LA, Marsh EE. Association between uterine fibroids and antim\u0026uuml;llerian hormone concentrations among African American women. Fertil Steril. 2022;117:832\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoini A, Kalhor M, Jahanian Sadatmahalleh S, Niknejadi M, Nasiri M, Yahyaei A, et al. Evaluation of the relationship between ovarian reserve with congenital anomalies and intramural uterine leiomyoma among infertile women: a cross-sectional study. J Ovarian Res. 2023;16:68.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Advanced glycation end products, skin autofluorescence, oxidative stress, uterine fibroids","lastPublishedDoi":"10.21203/rs.3.rs-9217861/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9217861/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUterine fibroids are common benign tumors in reproductive-age women and substantially impair quality of life. Advanced glycation end products (AGEs) have been implicated in ovarian disorders through oxidative stress, but their involvement in uterine fibroids remains unclear. This study aimed to examine the associations between AGE accumulation, oxidative stress, and uterine fibroids.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective observational study included 75 women undergoing infertility treatment between 2015 and 2018. AGE accumulation was assessed using skin autofluorescence (SAF). Serum diacron-reactive oxygen metabolites (d-ROMs) were measured as an index of oxidative stress, along with biochemical and reproductive hormone parameters. Associations with uterine fibroids were evaluated using logistic regression, elastic-net\u0026ndash;regularized variable selection, and exploratory mediation analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWomen with uterine fibroids exhibited significantly higher SAF and d-ROMs levels than women without gynecological disease. Both SAF and d-ROMs were associated with uterine fibroids in univariable analyses. However, in multivariable logistic regression, only d-ROMs remained independently associated with uterine fibroids. Exploratory mediation analysis suggested that d-ROMs statistically explained 46% of the association between SAF and uterine fibroids.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe present findings suggest that oxidative stress may be associated with uterine fibroids in women of reproductive age and may represent a potential biological correlate linking AGE accumulation to uterine fibroids.\u003c/p\u003e","manuscriptTitle":"Association of Oxidative Stress and Advanced Glycation End Products with Uterine Fibroids in Women of Reproductive Age: a Retrospective Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-24 08:07:01","doi":"10.21203/rs.3.rs-9217861/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-17T07:12:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-26T11:43:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T04:32:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T04:32:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2026-03-25T03:56:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc3eb263-6cc9-4034-8c6a-2f595f1a7380","owner":[],"postedDate":"April 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-24T08:07:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-24 08:07:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9217861","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9217861","identity":"rs-9217861","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}