1. Causal relationship between genetically predicted uterine leiomyoma and cancer risk: a two-sample Mendelian randomization
- Author
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Chenyang Zhao, Anquan Shang, Han Wu, Qiong Li, Lixiu Peng, and Chaoyan Yue
- Subjects
cancer ,causal association ,hormone ,Mendelian randomization ,uterine leiomyoma ,Diseases of the endocrine glands. Clinical endocrinology ,RC648-665 - Abstract
PurposeStudies have demonstrated that hormonal imbalance, such as elevated level of estrogen or reduced level of progesterone, was the main inducing factor of uterine leiomyoma (UL) development and some cancers. UL has been reported to be associated with several cancers in observational studies. However, the causal associations between UL and cancers remain unclear.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal associations between UL and 16 site-specific cancers using the public databases. Four methods, namely, the inverse variance weighting (IVW), MR-Egger, weighted median, and weighted mode, were applied in our MR analysis. Sensitivity tests were also performed to evaluate the robustness of these causal associations.ResultsThe IVW analysis indicated that genetically predicted UL increased the risk of low malignant potential ovarian cancer [odds ratio (OR) = 1.22, 95% confidence interval (CI): 1.06–1.40, p = 0.004], serous ovarian cancer (OR = 1.29, 95% CI: 1.10–1.52, p = 0.002), invasive mucinous ovarian cancer (OR = 1.24, 95% CI: 1.08–1.44, p = 0.003), clear cell ovarian cancer (OR = 1.25, 95% CI: 1.03–1.51, p = 0.023), breast cancer (OR = 1.07, 95% CI: 1.02–1.11, p = 0.002), and brain tumor (OR = 1.23, 95% CI: 1.06–1.42, p = 0.007). Conversely, genetically predicted UL reduced the risk of gastric cancer (OR = 0.91, 95% CI: 0.85–0.98, p = 0.008). The causal effects were consistent in the sensitivity analysis.ConclusionsOur results demonstrated that UL exhibits a causal relationship with high risk of several cancers. We suggest reinforcing the cancer screening in UL patients to enable the early detection of cancers.
- Published
- 2024
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