子宫内膜癌是一种常见的妇科肿瘤。在世界的一些地方,EC的发病率和死亡率呈上升趋势.了解EC的危险因素对于预防这种疾病的发生是必要的。观察性研究揭示了某些可改变的环境风险因素与EC风险之间的关联。然而,由于无法测量的混杂,测量误差,和反向因果关系,观察性研究有时判断稳健因果推论的能力有限。近年来,孟德尔随机化(MR)分析受到了广泛的关注,为癌症相关研究提供有价值的见解,并有望确定潜在的治疗干预措施。在MR分析中,使用遗传变异(等位基因在减数分裂期间随机分配,通常与环境或生活方式因素无关)代替可修改的暴露来研究危险因素与疾病之间的关系。因此,MR分析可以对暴露和疾病风险做出因果推断。这篇综述简要描述了MR分析的关键原则和假设;总结了已发表的关于EC的MR研究;重点讨论了不同风险因素与EC风险之间的相关性;并讨论了MR方法在EC研究中的应用。对EC的MR研究结果表明,2型糖尿病,子宫肌瘤,较高的体重指数,高级纤溶酶原激活物抑制剂-1(PAI-1),更高的空腹胰岛素,早期胰岛素分泌,端粒长度较长,较高的睾酮和较高的血浆皮质醇水平与EC风险增加相关.相比之下,初潮年龄较晚,高循环肿瘤坏死因子,低密度脂蛋白胆固醇较高,较高的性激素结合球蛋白水平与EC风险降低相关。总的来说,尽管有一些限制,MR分析仍为探讨不同危险因素与EC之间的因果关系提供了有效途径。
Endometrial cancer (EC) is a common gynecological cancer. In some parts of the world, the incidence and mortality of EC are on the rise. Understanding the risk factors of EC is necessary to prevent the occurrence of this disease. Observational studies have revealed the association between certain modifiable environmental risk factors and EC risk. However, due to unmeasured confounding, measurement errors, and reverse causality, observational studies sometimes have limited ability to judge robust causal inferences. In recent years, Mendelian randomization (MR) analysis has received extensive attention, providing valuable insights for cancer-related research, and is expected to identify potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly assigned during meiosis and are usually independent of environmental or lifestyle factors) is used instead of modifiable exposure to study the relationship between risk factors and disease. Therefore, MR analysis can make causal inference about exposure and disease risk. This
review briefly describes the key principles and assumptions of MR analysis; summarizes published MR studies on EC; focuses on the correlation between different risk factors and EC risks; and discusses the application of MR methods in EC research. The results of MR studies on EC showed that type 2 diabetes, uterine fibroids, higher body mass index, higher plasminogen activator inhibitor-1 (PAI-1), higher fasting insulin, early insulin secretion, longer telomere length, higher testosterone and higher plasma cortisol levels are associated with increased risk of EC. In contrast, later age of menarche, higher circulatory tumor necrosis factor, higher low-density lipoprotein cholesterol, and higher sex hormone-binding globulin levels are associated with reduced risk of EC. In general, despite some limitations, MR analysis still provides an effective way to explore the causal relationship between different risk factors and EC.