Causal relationship between renin-angiotensin system inhibitors and cancer: a two-sample, two-step Mendelian randomization study

Introduction

Renin-angiotensin system (RAS) inhibitors, specifically angiotensin-converting enzyme inhibitor (ACEI) and angiotensin receptor blocker (ARB), are the cornerstones in the treatment of hypertension (1). Due to their anti-inflammatory, antiproliferative, and antioxidant properties, ACEI/ARB are also widely used in patients with heart failure, coronary artery disease, diabetes, and chronic kidney disease (2). Therefore, any alteration in the disease risk associated with ACEI/ARB use could significantly impact a large population.

Although the RAS plays a crucial role in tumorigenesis (3), the impact of ACEI/ARB on cancer risk remains controversial, with some studies suggesting an increase (4,5) and others reporting a decrease (6,7) or no association (8,9). Clarifying the causal relationship between ACEI/ARB use and cancer is essential for reducing cancer incidence, alleviating healthcare costs, and mitigating societal burden. Therefore, there is an urgent need to apply more effective and reliable research methods to better elucidate this association.

Mendelian randomization (MR), a research method using single nucleotide polymorphisms (SNPs) as instrumental variables (IVs), offers a robust approach for assessing causal relationships between exposures and outcomes (10). Unlike traditional observational studies, MR analysis is less susceptible to confounding factors and reverse causality owing to the random segregation of alleles during meiosis (11). This study employed a two-sample, two-step MR analysis to explore the causal association between ACEI/ARB use and cancer and to investigate potential underlying mechanisms. We present this article in accordance with the STROBE-MR reporting checklist (available at https://cco.amegroups.com/article/view/10.21037/cco-2025-aw-131/rc).

Methods

Study design

This study utilized publicly available genome-wide association study (GWAS) summary statistics, eliminating the need for additional ethical approval or informed consent. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. We conducted two-sample, two-step MR analyses to assess the causal association between ACEI/ARB use and 24 site-specific cancers and to explore potential mediators. Mediators had to meet two criteria: (I) a causal relationship between the exposure and the mediator; (II) a causal relationship between the mediator and the outcome. Figure 1A outlines the study design.

Figure 1 Study design and diagram of this MR analysis. (A) Study design of this study. (B) Diagram of this MR. ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; GWAS, genome-wide association study; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; MR, Mendelian randomization; MR-PRESSO, Mendelian Randomization Pleiotropy Residual Sum and Outlier; SNP, single nucleotide polymorphism; VEGF, vascular endothelial growth factor.

Data sources

Genetic variant data related to ACEI/ARB prescription were sourced from the GWAS Catalog (https://www.ebi.ac.uk/gwas/), involving 62,752 ACEI/ARB users and 174,778 controls of European ancestry. Cancer-related genetic data were obtained from the GWAS Catalog, Integrative Epidemiology Unit (IEU) OpenGWAS project (https://gwas.mrcieu.ac.uk/), and FinnGen study (https://r11.finngen.fi/). The GWAS data for cancer were used in three stages: (I) in the discovery stage, we utilized cancer GWAS data from the GWAS Catalog and the IEU OpenGWAS project, as these datasets provided the largest number of cancer cases; (II) positive findings from the discovery stage were validated using data from the FinnGen study to assess the reproducibility of the results across independent databases; (III) further validation was conducted using data from East Asian populations to evaluate the consistency of the findings across different ethnic groups. Genetic variant data related to mediators were sourced from the GWAS Catalog and the IEU OpenGWAS project. Detailed information on the data used in this study can be found in Table S1.

Selection of IVs

SNPs related to exposure in GWAS data can be used as IVs to assess their causal association with different outcomes. To ensure the validity of the MR analysis, the selected IVs must satisfy the following three key assumptions: (I) IVs must be significantly associated with the exposure; (II) IVs must be independent of confounding factors that are related to the outcome; (III) IVs must be unrelated to the outcomes and must affect the outcomes solely through their influence on the exposure (12).

The process of selecting IVs for this study is illustrated in Figure 1B. First, SNPs significantly associated with the exposure at a genome-wide level (P<5×10⁻⁸) were extracted. Next, SNP clumping was conducted using the PLINK algorithm, with a linkage disequilibrium threshold of R²<0.001 and a window size of 10,000 kb, to remove SNPs in linkage disequilibrium. Third, SNPs with an F-statistic <10 were excluded to minimize potential bias from weak instruments. The F-statistic was calculated using the formula: F = R² (N −2)/(1− R²), where R² represents the proportion of variance in the exposures explained by the IVs, and N denotes the sample size. Fourth, a comprehensive query using the “FastTraitR” method was conducted to eliminate SNPs associated with confounders and outcomes. Finally, the remaining SNPs were used as IVs.

MR analysis

The selected IVs were harmonized with outcome data to remove palindromic and incompatible SNPs. This harmonization was performed using action 1 of the harmonise_data() function in the TwoSampleMR package. The MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) method was applied to identify and exclude outlier SNPs. The final set of SNPs was then used for MR analysis. The primary method for estimating causal effects was the inverse variance weighted (IVW) method, with complementary analyses using the MR-Egger slope test, weighted mode, weighted median, and simple mode methods.

Sensitivity analysis

To ensure the robustness of the study results and minimize potential biases, we conducted a series of sensitivity analyses. First, the Cochran’s Q test was applied to assess heterogeneity among IVs by comparing observed and expected effect sizes. Significant heterogeneity (P<0.05) warranted the use of a random-effects model in the IVW analysis. Second, MR-Egger regression for intercept was employed to detect horizontal pleiotropy. If pleiotropy remained significant (P<0.05) even after excluding outlier SNPs using MR-PRESSO, we considered re-evaluating GWAS dataset selection. Third, leave-one-out analysis was conducted by sequentially removing each SNP to assess whether the results were influenced by specific variants.

Statistical analysis

The MR analysis was conducted using R programming (version 4.4.1), primarily utilizing the “TwoSampleMR”, “FastTraitR”, “MRPRESSO”, and “metafor” R packages. The results are presented as odds ratio (OR) along with their 95% confidence intervals (CI), with all P values being two-tailed and P<0.05 considered statistically significant. The mediation effect was calculated using the formula β3 = β1 × β2, where β3 represents the mediation effect, β1 represents the effect of exposures on mediators, and β2 represents the effect of mediators on outcomes. Mediation proportions were calculated as β3/β, where β denotes the total effect obtained from the primary analysis. Standard errors and 95% CIs were calculated using the delta method.

Results

Causal association between ACEI/ARB and cancer

After removal of known confounders associated with cancer (including smoking and alcohol consumption), a total of 149 SNPs significantly associated with ACEI/ARB use were retained for harmonization. The MR analysis suggested that ACEI/ARB use causally reduces the risk of gastric cancer (OR =0.834, 95% CI: 0.766–0.908, P<0.001), colorectal cancer (OR =0.900, 95% CI: 0.834–0.971, P=0.006), lung cancer (OR =0.928, 95% CI: 0.873–0.987, P=0.02), breast cancer (OR =0.942, 95% CI: 0.892–0.994, P=0.03), and endometrial cancer (OR =0.900, 95% CI: 0.834–0.971, P=0.006) (Figure 2). No causal associations were observed between ACEI/ARB use and 19 other types of cancer (Table S2). The MR scatter plots visually illustrate the effect sizes of these associations (Figure S1). Although Cochran’s Q test detected heterogeneity, the IVW estimates remained significant after adjustment with the random-effects model. MR-Egger regression did not detect horizontal pleiotropy (Figure 2). Leave-one-out analysis found no significant influence of any single SNP on the causal inference, indicating that the causal association is not driven by any specific SNP (Figure S2).

Figure 2 Mendelian randomization results for the association between ACEI/ARB and cancer. ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; CI, confidence interval; IVW, inverse variance weighted; OR, odds ratio; SNPs, single-nucleotide polymorphisms.

Replication and validation

GWAS data from the FinnGen study were used to validate our findings across different datasets. The causal associations between ACEI/ARB use and the risks of colorectal cancer (OR =0.924, 95% CI: 0.855–0.999, P=0.05), lung cancer (OR =0.866, 95% CI: 0.795–0.944, P=0.001), and breast cancer (OR =0.900, 95% CI: 0.844–0.961, P=0.001) were consistent with the results from the discovery stage (Figure 3, Table S3).

Figure 3 Replication and meta-analyses for the causal effects between ACEI/ARB and cancer. ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; CI, confidence interval; GWAS, genome-wide association study; IVW, inverse variance weighted; OR, odds ratio; SNPs, single-nucleotide polymorphisms.

GWAS data from an East Asian cohort were utilized to further validate our results across different ethnic groups. The MR analysis revealed similar causal associations between ACEI/ARB use and the risks of gastric cancer (OR =0.806, 95% CI: 0.736–0.883, P<0.001), colorectal cancer (OR =0.791, 95% CI: 0.705–0.888, P<0.001), lung cancer (OR =0.866, 95% CI: 0.795–0.944, P=0.007), and breast cancer (OR =0.800, 95% CI: 0.712–0.901, P<0.001), supporting the robustness and generalizability of our findings (Figure 3, Table S3).

A meta-analysis of these results further confirmed the causal association between ACEI/ARB use and a reduced risk of gastric cancer (OR =0.831, 95% CI: 0.785–0.880, P<0.001, I²=0%), colorectal cancer (OR =0.878, 95% CI: 0.808–0.954, P=0.002, I²=63%), lung cancer (OR =0.893, 95% CI: 0.844–0.945, P<0.001, I²=29%), breast cancer (OR =0.891, 95% CI: 0.820–0.968, P=0.006, I²=73%), and endometrial cancer (OR =0.895, 95% CI: 0.834–0.961, P=0.002, I²=0%) (Figure 3). The MR scatter plots for these results can be found in Figures S3,S4. The leave-one-out analysis confirmed the stability of these findings across both validation stages (Figures S5,S6).

Two-step MR analysis

We screened potential mediating factors that might explain the association between ACEI/ARB use and a reduced cancer risk. Vascular endothelial growth factor A (VEGF-A), total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were identified as mediators (Table S4). The MR analysis of ACEI/ARB on these mediators revealed that ACEI/ARB use reduced VEGF-A (OR =0.971, 95% CI: 0.944–0.999, P=0.04), total cholesterol (OR =0.922, 95% CI: 0.910–0.934, P<0.001), and HDL-C (OR =0.960, 95% CI: 0.945–0.975, P<0.001), while increasing triglycerides (OR =1.022, 95% CI: 1.002–1.041, P=0.03) and LDL-C (OR =1.064, 95% CI: 1.045–1.084, P<0.001) (Figure 4A, Table S5).

Figure 4 Mendelian randomization results of causal effects between ACEI/ARB, mediators, and cancer. (A) Mendelian randomization results of causal effects between ACEI/ARB and mediators. (B) Mendelian randomization results of causal effects between mediators and cancers. ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; CI, confidence interval; HDL-C, high-density lipoprotein cholesterol; IVW, inverse variance weighted; LDL-C, low-density lipoprotein cholesterol; OR, odds ratio; SNPs, single-nucleotide polymorphisms; VEGF-A, vascular endothelial growth factor A.

In the MR analysis assessing mediators of cancer risk, elevated VEGF-A was causally associated with an increased the risk of colorectal cancer (OR =1.182, 95% CI: 1.023–1.365, P=0.02). Total cholesterol (OR =1.057, 95% CI: 1.002–1.114, P=0.04) and HDL-C (OR =1.098, 95% CI: 1.048–1.149, P<0.001) were causally associated with an increased risk of breast cancer, while HDL-C was causally associated with an increased risk of gastric cancer (OR =1.101, 95% CI: 1.002–1.209, P=0.05). Conversely, triglycerides were causally associated with a reduced risk of breast cancer (OR =0.946, 95% CI: 0.896–0.998, P=0.04), and LDL-C was causally associated with a reduced risk of gastric cancer (OR =0.811, 95% CI: 0.738–0.892, P<0.001) (Figure 4B, Table S6). MR scatter plots for these analyses can be found in Figures S7,S8. The leave-one-out analysis confirmed the stability of the two-step MR results (Figures S9,S10).

Mediation proportion

The mediation proportion results indicated that VEGF-A accounted for 4.72% of the mediating effect of ACEI/ARB on the reduction of colorectal cancer risk. LDL-C and HDL-C contributed 7.14% and 2.20%, respectively, to the reduction of gastric cancer risk. Total cholesterol, triglycerides, and HDL-C mediated 6.67%, 1.67%, and 6.67%, respectively, of the reduction risk in breast cancer (Table 1).

Discussion

To the best of our knowledge, this is the first systematic MR study investigating the causal relationship between ACEI/ARB use and cancer risk. Our findings suggest that ACEI/ARB use causally reduces the risk of gastric, colorectal, lung, breast, and endometrial cancers. Further mediation analyses indicate that the causal protective effect of ACEI/ARB on cancer risk is partially mediated by VEGF-A, total cholesterol, triglycerides, LDL-C, and HDL-C.

ACEI/ARB, a widely used class of medications, does not have major safety concerns, apart from their use in pregnancy, renal artery stenosis, and chronic kidney disease (13). The RAS plays a critical role in regulating cell proliferation, angiogenesis, and tumor progression (14). Our study found that ACEI/ARB use is causally associated with a reduced risk of gastric, colorectal, lung, breast, and endometrial cancer. These results align with several population-based cohort studies that report a similar relationship between ACEI/ARB use and a reduced risk of gastric cancer (15), colorectal cancer (16), lung cancer (17), and breast cancer (18). However, contradictory conclusions have been drawn in some other studies (19,20). These discrepancies across studies may stem from the inherent limitations of observational research, such as data inconsistencies, case report errors, and small sample sizes. Moreover, both ACEI/ARB users and cancer patients share common risk factors, including smoking and alcohol consumption. Observational studies are susceptible to these confounders, which can undermine the reliability of the conclusions. In contrast, our MR study uses genetic variants as IVs, effectively minimizing the impact of real-world confounding factors and reverse causality. By examining the causal relationship between ACEI/ARB and cancer risk at the genetic level, our study provides a more robust and reliable perspective on their causal relationship.

Our study identifies VEGF-A as a mediator in the reduction of colorectal cancer risk through ACEI/ARB. VEGF, a key regulator of angiogenesis, also plays a crucial role in tumor growth and metastasis (21). In mouse models, ACEI/ARB have been shown to inhibit VEGF expression, thereby suppressing the formation of blood and lymphatic vessels in gastrointestinal tumors (22). Our research further clarifies that ACEI/ARB may reduce colorectal cancer risk by inhibiting VEGF-A levels.

A meta-analysis of MR studies on cancer suggests a causal relationship between lipids and various cancers, including lung, breast, and endometrial cancers (23). Our study observed that ACEI/ARB use regulates lipid levels, decreasing total cholesterol and HDL-C while increasing triglycerides and LDL-C. Previous research has similarly reported that ARB can reduce total cholesterol and HDL-C levels, while increasing triglyceride and LDL-C levels. Notably, the observed increase in LDL-C levels has been attributed to the activation of peroxisome proliferator-activated receptor-γ (24). These findings are consistent with and further support the results of our study.

Our study also found that elevated HDL-C and total cholesterol levels are associated with an increased risk of breast cancer. A European prospective study confirmed a positive correlation between HDL-C levels and breast cancer risk (25). The mechanism may involve the glycosylation and oxidation of HDL, which can lead to abnormal adhesion of breast cancer cells to human umbilical vein endothelial cells and the extracellular matrix, thereby promoting the metastatic progression of breast cancer (26). A large prospective study in Korea found that high cholesterol levels were associated with a higher incidence of breast cancer [hazard ratio (HR) =1.17, P=0.03] (27). Although the exact mechanism by which total cholesterol contributes to cancer risk remains unclear, cancer cells, compared to normal cells, have higher levels of cholesterol-rich lipid rafts on their plasma membranes, which may play an important role in signaling pathways associated with cancer cell survival (28). Additionally, our study found that LDL-C and triglycerides are associated with a reduced risk of gastric and breast cancer. A large cohort study in Sweden also found a slight protective effect of triglycerides on breast cancer (29). A serum metabolomics study also revealed that higher LDL-C levels were related to a decreased risk of gastric cancer (HR =0.92, P<0.001), with LDL-C concentrations being lower in gastric cancer patients compared to normal or gastritis patients (30).

Angiotensin II (AT2) can promote tumor cell growth and proliferation by activating transforming growth factor-β, tyrosine kinase, and the mammalian target of rapamycin (3). ACEI/ARB may reduce cancer risk by inhibiting AT2. Additionally, activation of angiotensin type 1 receptor (AT1R) triggers mitogen-activated protein kinase, Janus kinase, and transcriptional activators, promoting tumor cell proliferation (31). AT1R is upregulated in various cancers, including breast, pancreatic, and lung cancers, and ARB can inhibit the expression of AT1R. Studies have shown that ACEI/ARB blockage results in amelioration of cancer through a variety of mechanisms (32).

The protective effects of RAS inhibitors were specific to certain cancers, which may be explained by biological heterogeneity. First, the RAS exhibits tissue-specific expression and activity. The density and function of AT2, AT1R, and other RAS components vary across different organs, which may render some tissue environments more susceptible to RAS modulation than others (33). Second, the relative importance of the mediating pathways we identified (VEGF-A and lipids) differs among cancer types. Finally, the inherent biological diversity of cancers means that a single intervention is unlikely to be universally effective. Therefore, the observed specificity of the effect aligns with the complex and multifactorial nature of carcinogenesis.

While our findings provide genetic evidence supporting a potential causal, protective effect of RAS inhibitors against several cancers, it is premature to propose their direct use as a broad cancer prevention strategy. RAS inhibitors, while generally safe for their indicated uses, are associated with side effects such as persistent cough, angioedema, hyperkalemia, and impaired renal function (34). The long-term safety profile of these drugs in healthy populations or individuals at low cardiovascular risk for the sole purpose of cancer prevention remains unestablished. Therefore, our results should be interpreted as generating a hypothesis and illuminating potential biological pathways that can be targeted. Future research should include randomized controlled trials specifically designed to assess the efficacy and safety of RAS inhibitors for cancer prevention in high-risk populations.

Our study has several strengths. First, we employed MR to explore the causal relationship between ACEI/ARB and cancer risk, providing a novel perspective that effectively eliminates common confounders in traditional epidemiological studies. Second, we implemented rigorous quality control measures and used multiple SNPs closely associated with ACEI/ARB. Third, we conducted several sensitivity analyses to confirm the consistency of the causal relationship. Finally, our results were validated across different databases and populations, which strengthens their robustness and generalizability.

Our study still has some limitations. First, although we performed several sensitivity analyses to minimize bias, completely eliminating bias is nearly impossible. Second, age is closely associated with cancer, and while there is a general overlap between ACEI/ARB users and cancer patients, we lack individual-level data to investigate the relationship between ACEI/ARB use and cancer across different age subgroups. Third, due to the absence of gender-specific and age-stratified GWAS summary statistics, we were unable to explore potential gender and age differences. Fourth, our analysis uses genetic variants to proxy long-term ACEI/ARB use, an inherent MR limitation that prevents us from analyzing specific treatment parameters like duration, dosage, drug initiation, or timing. Finally, pooling ACEI and ARB out of necessity may mask their opposing effects, so our result reflects the class’s average effect, warranting drug-specific future studies.

Conclusions

In conclusion, we conducted a comprehensive assessment of the causal relationship between ACEI/ARB use and cancer using MR method. The study provides genetic evidence that ACEI/ARB use causally reduces susceptibility to gastric, colorectal, lung, breast, and endometrial cancer, with this effect being partially mediated by VEGF-A, total cholesterol, triglycerides, LDL-C, and HDL-C. Our research provides robust genetic evidence supporting the role of ACEI/ARB in the prevention of multiple cancers.

Acknowledgments

This study was conducted by using GWAS data from the GWAS Catalog, the IEU OpenGWAS project, and the FinnGen database. We would like to thank all participants and the above mentioned consortiums for their contribution.

Footnote

Reporting Checklist: The authors have completed the STROBE-MR reporting checklist. Available at https://cco.amegroups.com/article/view/10.21037/cco-2025-aw-131/rc

Peer Review File: Available at https://cco.amegroups.com/article/view/10.21037/cco-2025-aw-131/prf

Funding: This study was supported by the Guangdong Basic and Applied Basic Research Foundation (No. 2023A1515010145).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cco.amegroups.com/article/view/10.21037/cco-2025-aw-131/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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