{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T12:55:07Z","timestamp":1790945707418,"version":"4.1.0"},"reference-count":71,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T00:00:00Z","timestamp":1690416000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background and objective<\/jats:title>\n                    <jats:p>Uterine leiomyoma is the most common benign tumor in females of reproductive age. However, its causes have never been fully understood. The objective of our study was to analyze the causal association between various factors and uterine leiomyoma using Mendelian randomization (MR).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Genetic variables associated with risk factors were obtained from genome-wide association studies. Summary-level statistical data for uterine leiomyoma were obtained from FinnGen and the UK Biobank (UKB) consortium. We used inverse variance weighted, MR-Egger, and weighted median methods in univariate analysis. Multivariable MR analysis was used to identify independent risk factors. A fixed-effect model meta-analysis was used to combine the results of the FinnGen and UKB data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In the FinnGen data, higher genetically predicted age at natural menopause, systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting insulin were associated with an increased risk of uterine leiomyoma, while higher age at menarche was associated with a reduced risk of uterine leiomyoma. Multivariable MR analysis of SBP and DBP showed that higher DBP might be an independent risk factor of uterine leiomyoma. In the UKB data, the results for age at natural menopause, SBP, DBP, and age at menarche were replicated. The result of the meta-analysis suggested that uterine leiomyoma could also be affected by polycystic ovary syndrome (PCOS), endometriosis, and 2-hour glucose level.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our MR study confirmed that earlier menstrual age, hypertension, obesity, and elevated 2-hour glucose post-challenge were risk factors for uterine leiomyoma, and the causal relationship between smoking and uterine leiomyoma was ruled out. In addition, later age of menopause and endometriosis were found to increase the risk of uterine leiomyoma, while PCOS was found to decrease the risk.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2023.1133260","type":"journal-article","created":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T20:39:23Z","timestamp":1690490363000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Genetic liability to multiple factors and uterine leiomyoma risk: a Mendelian randomization study"],"prefix":"10.3389","volume":"14","author":[{"given":"Yangming","family":"Qu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lanlan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shijie","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,7,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12939-020-01327-9","article-title":"Assessing burden, risk factors, and perceived impact of uterine fibroids on women's lives in rural Haiti: implications for advancing a health equity agenda, a mixed methods study","volume":"20","author":"Millien","year":"2021","journal-title":"Int J Equity Health"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra1209993","article-title":"Uterine fibroids","volume":"369","author":"Bulun","year":"2013","journal-title":"N Engl J Med"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1093\/humrep\/des263","article-title":"Uterine leiomyomata and fecundability in the right from the start study","volume":"27","author":"Johnson","year":"2012","journal-title":"Hum Reprod"},{"key":"B4","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1016\/j.ajog.2009.12.013","article-title":"Inpatient hospitalization for gynecologic disorders in the united states","volume":"202","author":"Whiteman","year":"2010","journal-title":"Am J Obstet Gynecol"},{"key":"B5","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.bpobgyn.2017.09.004","article-title":"Epidemiology and risk factors of uterine fibroids","volume":"46","author":"Pavone","year":"2018","journal-title":"Best Pract Res Clin Obstet Gynaecol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1007\/s00439-021-02312-0","article-title":"Genetic analyses of gynecological disease identify genetic relationships between uterine fibroids and endometrial cancer, and a novel endometrial cancer genetic risk region at the WNT4 1p36","volume":"140","author":"Kho","year":"2021","journal-title":"12 locus. 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