Ovarian cancer is a kind of cancer that occurs in female ovarian tissue. There are many pathological subtypes, among which high-grade serous ovarian cancer (1) is the most common. In developed countries, ovarian cancer is the main cause of death among all gynecological cancers (2). Due to the lack of specific signs and symptoms at the early stages of the disease, ovarian cancer is usually found in late stage, with extensive peritoneal (Phase III) or extraperitoneal (Phase IV) spread. Tumor reduction surgery and platinum and taxane drug chemotherapy could make 75% of patients achieve clinical remission. At present, the 5-year survival rate of ovarian cancer patients is roughly less than 30% (3–5). There are many risk factors for ovarian cancer, including age, reproductive history, changeable lifestyle factors, family history and gene mutation (6).

Insulin (7) is the main regulator of glucose, lipid and protein metabolism. When oral glucose load or mixed meal is ingested, plasma glucose concentration increases, and islets of β Cells are stimulated to secrete insulin. Insulin can inhibit the production of endogenous glucose (the main target organ is the liver), stimulate the uptake and storage of glucose by muscle, liver and fat cells, and inhibit the decomposition of fat, leading to a decrease in plasma free fatty acids concentration (8), which helps to inhibit the production of glucose in the liver and increase the uptake of glucose in the muscle, and can relax muscle vessels, which helps to enhance muscle glucose disposal.

The incidence rate of various cancers is higher in patients with insulin secretion disorder (especially in patients with type 2 diabetes). Many studies and observations in the field of overseas studies have confirmed this view. It is reported that among patients with type 2 diabetes, the relative risk of endometrial cancer, liver cancer and pancreatic cancer is more than 2 times, while the relative risk of bladder cancer, breast cancer and colorectal cancer is as high as 1.5 times (9–12). In addition to the increase in incidence rate, the overall mortality rate of diabetes patients when diagnosed with cancer is higher (13) than that of the non-disease group. Systematic reviews (14, 15) could suggest that overweight people have a higher risk of ovarian cancer, and the risk of ovarian cancer increases with obesity. The increase and abnormality of obesity or body mass index often could lead to the disorder of endocrine system in the human body, such as insulin resistance, estrogen level change and other characteristics, which are factors that cannot be ignored in the role of obesity factors in weight related cancer.

Therefore, it is important to understand the hormone specific relationship between metabolism and cancer (16). In this paper, bidirectional mendelian randomization analysis was used to confirm the causal relationship between insulin related characteristics and ovarian cancer risk.

Six insulin related indicators, including Fasting blood insulin, Fasting blood insulin adjusted for BMI, Insulin secret rate, Peak insulin response, Acute insulin response and Insulin disposition index, went Two-sample bidirectional MR with ovarian cancer. We conducted a total of 12 statistical tests in 6 groups.

As shown in Table 2 , we summarize all positive MR results into this table. The insulin secretion rate was statistically significant (IVW, p<0.05).

On the contrary, the other five insulin related indicators (Fasting blood insulin, Fasting blood insulin adjusted for BMI, Peak insulin response, Acute insulin response and Insulin disposition index) did not show any correlation with the risk of ovarian cancer ( Supplementary Figures S1 - S5 ).

When taking insulin secretion rate as the exposure factor, we found that impaired insulin secretion was associated with an increased risk of ovarian cancer (OR 0.9991305 (0.9984108, 0.9998507), p=0.017968, Figure 1 ), which was confirmed in the positive MR analysis ( Figure 2 ). There were 9 SNPs related to the above results (rs10830963, rs10983538, rs11135317, rs138478706, rs1779638, rs58858201, rs7756992, rs9425530, rs9479886), and the details were shown in S-Table 1 of Supplementary Materials . For the pleiotropy test of MR analysis, no obvious pleiotropy was found (p>0.05, Table 2 ). The retention analysis of the above results shows that all SNPs are generally stable ( Figure 3 ), and the funnel plot did not show significant heterogeneity ( Supplementary Figure S6 ).

However, we still got statistically significant results (IVW, p<0.05) when we performed reverse MR analysis on the insulin secret rate. That was to say, with ovarian cancer as the exposure factor and the insulin secret rate as the outcome variable, we still got the causal relationship of the above two parties (OR 3.092427e-13 (3.816945e-23, 2.505434e-03), p=0.013, Figure 4 ), which was confirmed in the inversive MR analysis ( Figure 5 ). The above results indicate that ovarian cancer had a causal relationship with human insulin secret rate. In order to test the reliability of the above results, we conducted Cochran’s Q test (p=0.4528141) and pleiotropy test (p=0.6568936). However, these test results indicate that the above results do not have the pleiotropy and heterogeneity of imaging conclusions. There were 10 SNPs related to the above results (rs114858887, rs1358253, rs1687403, rs2143612, rs28678815, rs35486093, rs4443540, rs76264086, rs78231145, rs79693379), and the details were shown in S-Table 2 of Supplementary Materials . The retention analysis of the above results showed that all SNPs were generally stable ( Figure 6 ), and the funnel plot did not show significant heterogeneity ( Supplementary Figure S7 ).

This study is a Bidirectional Mendelian Randomization Study, which used MR to analyze the two-way causal relationship between insulin related traits and the risk of ovarian cancer. We found that the insulin secretion rate has a two-way causal relationship with ovarian cancer, which is rarely reported.

Insulin is an important hormone in mammalian homeostasis regulation, which regulates metabolism together with glucagon antagonism. The insulin secretion rate provides an estimate of the insulin secretion rate before hepatic insulin clearance (25). The main physiological stimulation of insulin secretion is the increase of circulating glucose concentration in the postprandial state. Impaired insulin secretion is often associated with high body mass index, and a large number of statistics have proved the association between overweight and ovarian cancer (15, 26). As mentioned in the introduction of this article, impaired insulin status is associated with the risk or survival of many cancers.

By analyzing the MR results in this paper, we could easily find that impaired insulin secretion was associated with an increased incidence of ovarian cancer. We will analyze the influence of insulin secretion on ovarian cancer from the following aspects. First, from the perspective of insulin and tumor cell energetics, compared with healthy cells, ovarian cancer tumor cells have a huge energy demand to support the abnormal proliferation and metastasis of tumors. Compared with normal human cells, tumor cells tend to change their metabolic mode, such as the transformation of primary glucose utilization pathway from oxidative phosphorylation to glycolysis, namely Warburg effect (27). Insulin also controls systemic and intracellular metabolism through substrate (glucose) distribution (28). However, tumors have changes in PI3K mTOR signaling pathway, and mTOR also changes the availability of glucose in tumor cells by regulating glucose uptake and glycogen decomposition (29). At the same time, anti-tumor drugs targeting systemic glucose homeostasis and tumor growth regulation have also entered the clinical trial stage (30). Second, impaired insulin secretion is associated with glucagon. Hyperinsulinemia is associated with the increased risk of breast cancer (31), endometrial cancer (32), ovarian cancer (33) and prostate cancer (34), and is closely related to the increased mortality of pancreatic cancer and breast cancer (35, 36), and some studies indicate that glucagon increases the overall mortality of cancer (37). However, it should be noted that many studies have pointed out that the postmenopausal serum insulin level is not related or is very weak to ovarian cancer after adjustment and correction (33, 38), which is consistent with the negative results of this study. However, we found that the significant results are insulin secretion rather than simple serum levels. At the same time, there is no denying that insulin and glucagon, which are hormones, are closely related to lipid peroxidation and metabolism (39), fibroblast growth factor receptor-1 (40), and inflammatory cytokines (41), and these factors undoubtedly play a key role in the progress of cancer. Third, the repeated mention of obesity or overweight is undoubtedly related to impaired insulin secretion. Ovarian cancer cells use fat cells as a source of energy for growth and migration (42). At the same time, as metabolic disorders, their internal metabolism affects each other. Because of changes in lifestyle factors, the prevalence of metabolic disorders is increasing year by year worldwide, just as obesity, type II diabetes and metabolic syndrome are all associated with ovarian cancer (43–46). A recent meta-analysis (47) showed that the risk of diabetes and OC was weak but still related, and many studies had many bias or confounding factors. It has also been pointed out that despite normal BMI, people with unhealthy metabolism or central obesity have a higher risk of cancer (48). Fourth, insulin is also related to immunity. Insulin (49) is related to regulating different immune phenotypes and responses, and the expression of insulin receptors on T cells, B cells and macrophages proves this view (50).

At the same time, another study showed that the existence of ovarian cancer was related to insulin secretion. The mechanism involved in this is very complex, because the metabolism of tumor variant fish is very complex. We speculate that the anaerobic glycolysis of tumors occupies the main form of metabolism, and pentose phosphate shunt pathway and its nucleotide products (51) play a certain role in the regulation of insulin secretion. Among them, glucose-6-phosphate dehydrogenase (G6PDH) (52) can explain the impairment of insulin secretion by islet cells through the impairment of NADPH production, and the 6-phosphogluconate dehydrogenase (6PGDH) (53) negative impact is attributed to the accumulation of intermediate metabolites of this pathway, leading to the activation of extracellular regulated kinase (ERK). Currently, it is known that ERK (53) can promote insulin transcription in response to acute signals, but its continuous activation may lead to β Cell dysfunction and apoptosis.

These studies have many defects and deficiencies, as follows: (1) Avoiding the pleiotropy of SNPs selected as instrumental variables is an important principle to ensure the accuracy of MR analysis. Usually, MR Egger intercept and MR-PRESSO methods are used to detect horizontal pleiotropy to reduce bias, but the method is not absolute for detection of pleiotropy. The MR analysis results of this study did not find heterogeneity and level pleiotropy, which proved the robustness of the results, but still could not completely rule out the interference of potential pleiotropy. This limitation is due to the existing analysis methods, and there are also some works (54) exploring other multiple validity testing methods. (2) The Insulin related Trains included in this study may lack some indicators. When selecting indicators, we selected open and common indicators. For the selection of databases, we also selected databases based on the same species, recent time and large number of people. However, this may not fully represent the function and release of insulin. We try to avoid these limitations, but it is undeniable that they may still exist. (3) There is also the race problem in the database. In order to control the same race, we try to select European samples, which will undoubtedly affect the conclusion to be extended to other colored people. (4) The sample size of some indicators may not be enough to avoid bias, which is also caused by database restrictions.

Through the Bidirectional Mendelian Randomization analysis, we obtained the two-way causal relationship between the insulin secret rate and ovarian cancer, that is, the reduction of the insulin secret rate is related to the risk of ovarian cancer, and the occurrence of ovarian cancer also has an impact on the insulin secret rate. When this research needs large sample data research in the real world, we hope to have research to further verify this conclusion.

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

XW wrote the main manuscript. JL and LC developed the model, WL and JS collected and analyzed the data. ZY reviewed and revised the manuscript. ZW and HL designed the study. Other personnel participate in discussion and article revision. All authors contributed to the article and approved the submitted version.