AUTHOR=Guo Jian-Zeng , Wu Qi-Jun , Liu Fang-Hua , Gao Chang , Gong Ting-Ting , Li Gang 

TITLE=Review of Mendelian Randomization Studies on Endometrial Cancer

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.783150

DOI=10.3389/fendo.2022.783150

ISSN=1664-2392

ABSTRACT=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 confusion, measurement errors, and reverse causality, observational studies cannot give 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 is used instead of modifiable exposure to study the relationship between risk factors and disease. Therefore, MR analysis can make causal conclusions about exposure and disease risk. This review provides a comprehensive overview of the key principles and assumptions of MR analysis. Summarizes the published MR research, focusing on the causal relationship between different risk factors and EC risk, and comprehensively analyzes the MR method and its future applications. The results of MR studies on EC showed that type 2 diabetes, higher body mass index, higher fasting insulin, early insulin secretion, longer telomere Length, higher circulatory leptin, circulatory sOB-R, and higher testosterone levels are associated with increased risk of EC. In contrast, later age of menarche, higher circulatory tumor necrosis factor, low-density lipoprotein cholesterol, and 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.