Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
Front Endocrinol (Lausanne). 2023 Mar 1;14:1131767. doi: 10.3389/fendo.2023.1131767. eCollection 2023.
It is well known that the occurrence and development of ovarian cancer are closely related to the patient's weight and various endocrine factors in the body.
Mendelian randomization (MR) was used to analyze the bidirectional relationship between insulin related characteristics and ovarian cancer.
The data on insulin related characteristics are from up to 5567 diabetes free patients from 10 studies, mainly including fasting insulin level, insulin secretion rate, peak insulin response, etc. For ovarian cancer, UK Biobank data just updated in 2021 was selected, of which the relevant gene data was from 199741 Europeans. Mendelian randomization method was selected, with inverse variance weighting (IVW) as the main estimation, while MR Pleiotropy, MR Egger, weighted median and other methods were used to detect the heterogeneity of data and whether there was multi validity affecting conclusions.
Among all insulin related indicators (fasting insulin level, insulin secretion rate, peak insulin response), the insulin secretion rate was selected to have a causal relationship with the occurrence of ovarian cancer (IVW, P < 0.05), that is, the risk of ovarian cancer increased with the decrease of insulin secretion rate. At the same time, we tested the heterogeneity and polymorphism of this indicator, and the results were non-existent, which ensured the accuracy of the analysis results. Reverse causal analysis showed that there was no causal effect between the two (P>0.05).
The impairment of the insulin secretion rate has a causal effect on the risk of ovarian cancer, which was confirmed by Mendel randomization. This suggests that the human glucose metabolism cycle represented by insulin secretion plays an important role in the pathogenesis of ovarian cancer, which provides a new idea for preventing the release of ovarian cancer.
众所周知，卵巢癌的发生和发展与患者的体重和体内各种内分泌因素密切相关。
采用孟德尔随机化（MR）分析胰岛素相关特征与卵巢癌之间的双向关系。
胰岛素相关特征数据来自 10 项研究中多达 5567 名无糖尿病患者，主要包括空腹胰岛素水平、胰岛素分泌率、峰值胰岛素反应等。对于卵巢癌，选择了 2021 年最新更新的英国生物库数据，其中相关基因数据来自 199741 名欧洲人。选择孟德尔随机化方法，以逆方差加权（IVW）作为主要估计，同时使用 MR 异质性、MR Egger、加权中位数等方法检测数据的异质性和是否存在多效性影响结论。
在所有胰岛素相关指标（空腹胰岛素水平、胰岛素分泌率、峰值胰岛素反应）中，选择胰岛素分泌率与卵巢癌的发生具有因果关系（IVW，P<0.05），即随着胰岛素分泌率的降低，卵巢癌的风险增加。同时，我们检测了该指标的异质性和多态性，结果不存在，保证了分析结果的准确性。反向因果分析表明两者之间没有因果关系（P>0.05）。
胰岛素分泌率的损害对卵巢癌的风险有因果关系，这一点被孟德尔随机化所证实。这表明以胰岛素分泌为代表的人类葡萄糖代谢循环在卵巢癌的发病机制中起着重要作用，为预防卵巢癌的发生提供了新的思路。
