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. 2025 Nov 26;14(11):7700–7711. doi: 10.21037/tcr-2025-1168

Causal relationship between hypertension and cancer: a two‑sample bidirectional Mendelian randomization study

Chenggong Zeng 1,2,3,#, Juanhua Zhu 4,#, Yan Mao 1,2,3,#, Xi Zhen 5, Zhiqing Wei 1,2,3, Zijun Zhen 1,2,3,✉
PMCID: PMC12686201  PMID: 41378016

Abstract

Background

Evidence from observational studies suggests that the association between hypertension and cancer is controversial, likely due to confounding factors and reverse causality. This study employs Mendelian randomization (MR) to investigate the causal relationship between hypertension and various cancers.

Methods

We conducted two‑sample bidirectional MR analyses using genetic variants associated with hypertension (484,598 participants) and 17 site-specific cancers from various genome-wide association studies (GWAS) including the GWAS Catalog, Integrative Epidemiology Unit OpenGWAS project, and FinnGen study. GWAS data on anti-hypertensive drugs prescription were used to explore potential mechanisms. The primary analysis employed the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, weighted mode, and simple mode methods. Heterogeneity and pleiotropy were assessed using Cochran’s Q, the MR-Egger intercept test, the MR pleiotropy residual sum and outlier test, leave-one-out analysis, funnel plots, and MR-Robust Adjusted Profile Score analysis. Genetic instruments were selected based on genome-wide significance (P<5×10−8), LD clumping (r2<0.001, window =10,000 kb), and F-statistic >10. Single nucleotide polymorphisms (SNPs) associated with confounders (smoking or alcohol consumption) and the outcome were removed using FastTraitR.

Results

We identified a potential causal relationship between hypertension and a decreased risk of gastric cancer [odds ratio (OR) =0.615, 95% confidence interval (CI): 0.415–0.912, P=0.02] and colorectal cancer (OR =0.708, 95% CI: 0.516–0.971, P=0.03). MR estimates were consistent in East Asian populations (gastric cancer, OR =0.573, P=0.01; colorectal cancer, OR =0.466, P=0.001) and directionally similar in the FinnGen cohort. Reverse MR analysis indicated an inverse association of lymphoma with hypertension risk (OR =0.992, 95% CI: 0.985–1.000, P=0.044), whereas genetic predisposition to thyroid cancer was positively associated with hypertension (OR =1.008, 95% CI: 1.002–1.013, P=0.01). Further investigation identified inverse associations between gastric cancer risk and the use of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) (OR =0.834, P<0.001), beta-blockers (OR =0.753, P<0.001), and calcium channel blockers (CCBs) (OR =0.794, P<0.001). Similar effects were observed for colorectal cancer with ACEI/ARB (OR =0.931, P=0.03), beta-blockers (OR =0.900, P=0.01), CCB (OR =0.912, P=0.008), and diuretics (OR =0.917, P=0.03).

Conclusions

Our MR analyses suggested that genetic predisposition to hypertension was associated with a reduced risk of gastric and colorectal cancer. This inverse relationship may be mediated by biological pathways that are targeted by antihypertensive drugs, highlighting a potential mechanistic link worthy of further clinical investigation.

Keywords: Hypertension, cancer, anti-hypertensive drugs, Mendelian randomization (MR), causal relationship

Highlight box.

Key findings

• This study suggests that genetic predisposition to hypertension is associated with a reduced risk of gastric and colorectal cancer.

What is known and what is new?

• Evidence from observational studies suggested that hypertension may decrease cancer risk.

• By investigating the association between hypertension and cancer at the genetic level, our study offers a more robust and reliable perspective on their causal relationship.

What is the implication, and what should change now?

• This study proves that hypertension is associated with a reduced risk of gastric and colorectal cancer. This inverse relationship may be mediated by biological pathways that are targeted by antihypertensive drugs, highlighting a potential mechanistic link worthy of further clinical investigation. Further studies can explore the related mechanisms and targets to develop relevant drugs for cancer prevention.

Introduction

Hypertension is a global health crisis, affecting over one billion individuals worldwide, with its prevalence increasing significantly with age, particularly among the elderly (1-3). The pathogenesis of hypertension involves a complex interplay of genetic predisposition, environmental triggers, and socioeconomic factors (4). As a leading risk factor for cardiovascular diseases, stroke, and chronic kidney disease (5), hypertension is typically managed through five classes of medications: angiotensin-converting enzyme inhibitor/angiotensin receptor blockers (ACEI/ARBs), beta-blockers, calcium channel blockers (CCBs), diuretics, and alpha-blockers (6).

Similarly, cancer predominantly affects older populations and is the second leading cause of global mortality (7). Hypertension and cancer share common risk factors, such as advanced age, smoking, alcohol consumption, unhealthy dietary, and environmental influences (8). Moreover, both diseases demonstrate overlapping pathophysiological mechanisms characterized by chronic inflammation and systemic oxidative stress (8,9). Consequently, a significant proportion of patients are suffered from both hypertension and cancer. However, the relationship between the two diseases remains controversial. Some cohort studies suggest hypertension as a risk factor for cancer (10-14), while others report an inverse association (15,16) or find no correlation (17,18). Clarifying the causal relationship between hypertension and cancer is crucial for reducing disease burden, alleviating healthcare costs, and mitigating societal impacts. Therefore, there is an urgent need for more robust and reliable research methodologies to better elucidate their association.

Mendelian randomization (MR) is a powerful research method that utilizes single nucleotide polymorphisms (SNPs) associated with exposure as instrumental variables (IVs) to investigate causal effects of traits or phenotypes on outcomes (19). Due to the random distribution of genetic variants during meiosis, MR analysis functions similarly to a randomized controlled trial, minimizing susceptibility to confounders and reverse causality. This study aims to conduct bidirectional two-sample MR analyses to comprehensively assess the causal relationships between hypertension and 17 site-specific cancers, while also exploring potential underlying mechanisms. We present this article in accordance with the STROBE-MR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1168/rc).

Methods

Study design

This study employed bidirectional two-sample MR analyses using Genome-wide association study (GWAS) summary statistics from European populations to explore the causal relationships between hypertension and 17 site-specific cancers. The MR analysis adhered to the “Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization” guidelines (20). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Given that all exposure and outcome data were sourced from publicly available GWAS summary statistics, no additional ethical approval or informed consent was required. To further validate our findings, we replicated the analyses using independent datasets and GWAS data from other ethnic groups. Moreover, we performed additional MR analyses to explore potential mechanisms underlying the observed causal associations between hypertension and cancer. An overview of the study design, including the selection of IVs and the analytical workflow, is provided in Figure 1.

Figure 1.

Figure 1

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Study design and diagram of this Mendelian randomization analysis. (A) Study design of this study. (B) Diagram of this Mendelian randomization. GWAS, genome-wide association study; MR, Mendelian randomization; MR-PRESSO, Mendelian Randomization Pleiotropy Residual Sum and Outlier; SNP, single-nucleotide polymorphism.

Data sources

Genetic variants associated with hypertension were obtained from the GWAS Catalog (https://www.ebi.ac.uk/gwas/). Hypertension was defined according to the International Classification of Diseases-10 criteria, which stipulate a confirmed office blood pressure measurement of systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, after excluding cases influenced by acute illness or medication. This study utilized GWAS data for hypertension comprising 129,909 cases and 354,689 controls of European ancestry, all recruited in 2021. Genetic variants related to cancer were sourced from the GWAS Catalog, the Integrative Epidemiology Unit (IEU) OpenGWAS project (https://gwas.mrcieu.ac.uk/), and the FinnGen study (https://r11.finngen.fi/). The GWAS data for cancer were used in three stages: (I) in the discovery stage, we used cancer 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 FinnGen study to assess the reproducibility of the results across independent databases; (III) further validation was conducted using GWAS data from East Asian populations to evaluate the consistency of the findings across different ethnic groups. The discovery stage included 17 site-specific cancers: lung cancer, gastric cancer, colorectal cancer, esophageal cancer, pancreatic cancer, liver cancer, breast cancer, ovarian cancer, cervical cancer, endometrial cancer, prostate cancer, bladder cancer, kidney cancer, thyroid cancer, skin cancer, brain cancer, and lymphoma. To explore potential mechanisms underlying the causal relationship between hypertension and cancers, genetic variants associated with anti-hypertensive drugs prescription (ACEI/ARB, beta-blockers, CCB, diuretics, and alpha-blockers) were also obtained from the GWAS Catalog. The drug prescription data were derived from self-reported medication records. Detailed information on the datasets and their sources is provided in Table S1.

Selection of IVs

SNPs associated with the exposure in the GWAS data can be used as IVs to assess their causal effects on different outcomes. To ensure the validity of the MR analysis, the selected IVs must satisfy the following three key assumptions: (I) IVs must be strongly associated with the exposure; (II) IVs should not be associated with any confounders that could distort the exposure-outcome relationship; and (III) IVs must be unrelated to the outcomes and must affect the outcomes solely through their influence on the exposure (21).

The process of IVs selection for this study is illustrated in Figure 1. First, SNPs significantly associated with the exposure at a genome-wide level (P<5×10−8) were extracted. Next, SNPs clumping was conducted using the PLINK algorithm with a linkage disequilibrium threshold of r2<0.001 and a windows 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 [smoking and alcohol consumption (22,23)] and outcomes. Finally, SNPs that passed all selection criteria were retained as valid IVs, ensuring a strong and reliable association with the exposure.

MR analysis

The IVs selected through the above process were harmonized with the outcome data to remove palindromic and incompatible SNPs. This harmonization was performed using action 1 of the harmonise_data() function in the TwoSampleMR package. To mitigate the impact of horizontal pleiotropy on causal estimates, we applied the Mendelian Randomization Pleiotropy Residual Sum and Outlier (MR-PRESSO) method to identify and exclude outlier SNPs (24). 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, which calculates a weighted average of effects estimates from each genetic variant based on their variances and co-variances (25). The MR-Egger slope test, weighted mode, weighted median, and simple mode methods were conducted as complementary analyses to further validate the IVW estimates.

Sensitivity analysis

To ensure the robustness of our findings and minimize potential biases, several sensitivity analyses were conducted. First, the Cochran’s Q test was applied to assess heterogeneity among IVs by comparing observed and expected effect sizes (26). Significant heterogeneity (P<0.05) warranted the use of a random-effects model in the IVW analysis (27). Second, MR-Egger regression for intercept was employed to detect horizontal pleiotropy, which represents the average pleiotropic effect of all genetic variants (28). A P value <0.05 indicated the presence of horizontal pleiotropy. If pleiotropy remained significant 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 any single variant disproportionately influenced the results. Fourth, the funnel plot was primarily used to visually assess quantitative bias among the genetic instruments by checking for asymmetry in the scatter of variant-specific estimates. Finally, Mendelian Randomization-Robust Adjusted Profile Score (MR-RAPS) analysis was conducted to assess the degree of sample overlap.

Statistical analysis

All MR analyses were conducted using R programming (version 4.4.1). The primary R packages used in this study included “TwoSampleMR”, “FastTraitR”, and “MRPRESSO”. Results were reported as odds ratio (OR) with 95% confidence interval (CI), and all P values were two-sided, with statistical significance set at P<0.05.

Results

Causal association between hypertension and cancer

After exclusion of confounders for cancer, a total of 167 SNPs significantly associated with hypertension were retained for harmonization (Figure 1B). Detailed information on the SNPs selected as IVs and the number of SNPs retained after each selection step are provided in Tables S2,S3, respectively. The MR analysis revealed that hypertension was associated with a decreased risk of gastric cancer (OR =0.615, 95% CI: 0.415–0.912, P=0.02) and colorectal cancer (OR =0.708, 95% CI: 0.516–0.971, P=0.03) (Figure 2A). However, no causal associations were identified between hypertension and other 15 types of cancer (Table S4). Scatter plots of the MR analyses were used to illustrate the effect sizes of hypertension on different cancer types (Figure S1), while forest plots depicted the effect estimates for each individual SNP (Figure S2). The funnel plot of SNP distributions was symmetrical, indicating no substantial quantitative bias (Figure S3). Although Cochran’s Q test indicated heterogeneity in the causal estimates for gastric and colorectal cancer, the significance of the IVW estimates remained robust after adjustment using a random-effects model. MR-Egger regression for intercept detected no evidence of horizontal pleiotropy (Figure 2A). Further validation through leave-one-out analysis confirmed that no single SNP significantly impacted the causal inference, suggesting that the observed associations between hypertension and gastrointestinal cancer were not driven by any specific SNP (Figure S4).

Figure 2.

Figure 2

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Mendelian randomization and reverse results for the association between hypertension and cancer risk. (A) Mendelian randomization results of causal effects between hypertension and cancer risk. (B) Mendelian randomization results of causal effects between cancer and hypertension risk. CI, confidence interval; IVW, inverse variance weighted; OR, odds ratio; SNP, single-nucleotide polymorphism.

Causal association between cancer and hypertension

Using genetic liability for cancer as the exposure and hypertension as the outcome, we conducted a reverse MR analysis to investigate the causal effect of cancer on hypertension. The MR results indicated that lymphoma was associated with a slightly reduced risk of hypertension (OR =0.992, 95% CI: 0.985–1.000, P=0.04), while thyroid cancer was associated with a slightly increased risk of hypertension (OR =1.008, 95% CI: 1.002–1.013, P=0.01) (Figure 2B). Detailed information on the SNPs selected as IVs for lymphoma and thyroid cancer was presented in Tables S5,S6. No significant causal associations were observed between the remaining eight cancer types and hypertension (Table S7). Furthermore, MR analysis could not be performed for ovarian, bladder, cervical, kidney, pancreatic, brain, and esophageal cancers due to an insufficient number of IVs. The MR scatter plots for these results can be found in Figure S5. The random-effects IVW model confirmed the robustness of the results under the existence of heterogeneity, and MR-Egger regression intercept test found no evidence of horizontal pleiotropy (Figure 2B). Leave-one-out analysis confirmed the stability of the results (Figure S6).

Replication and validation

GWAS data from the FinnGen study was utilized to validate our results across independent datasets. The results showed that the effect of hypertension on gastric cancer (OR =0.512, 95% CI: 0.246–1.065, P=0.07) and colorectal cancer (OR =0.788, 95% CI: 0.542–1.144, P=0.21) was directionally consistent with the associations observed in the discovery stage (Table S8). GWAS data from East Asian cohort were used to validate our findings across different ethnic groups. The results confirmed a significant association between hypertension and a reduced risk of gastric cancer (OR =0.573, 95% CI: 0.374–0.879, P=0.01) and colorectal cancer (OR =0.466, 95% CI: 0.291–0.745, P=0.001) for East Asian populations. No evidence of horizontal pleiotropy was detected (Figure 3). The leave-one-out analysis confirmed the stability of these findings across both validation stages (Figures S7,S8). Meta-analysis integrating results from multiple datasets strongly reinforced the inverse association between hypertension and gastric cancer (OR =0.583, 95% CI: 0.446–0.764, P<0.001, I2=0%) and colorectal cancer (OR =0.664, 95% CI: 0.513–0.860, P=0.002, I2=28%). These findings further reinforce the robustness and consistency of the causal associations identified in our study.

Figure 3.

Figure 3

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Replication and meta-analyses for the causal effects between hypertension and gastrointestinal cancer risk. CI, confidence interval; GWAS, genome-wide association study; IVW, inverse variance weighted; OR, odds ratio; SNP, single-nucleotide polymorphism.

Investigation of potential mechanism

To explore the potential mechanisms behind the reduced risk of gastrointestinal cancers due to hypertension, we hypothesize that certain anti-hypertensive drugs may exert tumor-suppressive effects. This hypothesis is supported by several retrospective studies (29-32). To validate this proposition, we conducted two-sample MR analyses using GWAS data on anti-hypertensive medications (ACEI/ARB, beta-blockers, CCB, diuretics, and alpha-blockers) as exposures. Detailed information on the SNPs selected as IVs for ACEI/ARB, beta-blockers, CCB, diuretics, and alpha-blockers was presented in Tables S9-S13. MR analysis revealed a significant inverse association of ACEI/ARB (OR =0.834, 95% CI: 0.766–0.908, P<0.001), beta-blockers (OR =0.753, 95% CI: 0.679–0.836, P<0.001), and CCB (OR =0.794, 95% CI: 0.700–0.900, P<0.001) with gastric cancer. Similarly, ACEI/ARB (OR =0.931, 95% CI: 0.872–0.994, P=0.03), beta-blockers (OR =0.900, 95% CI: 0.829–0.978, P=0.01), CCB (OR =0.912, 95% CI: 0.851–0.977, P=0.008), and diuretics (OR =0.917, 95% CI: 0.851–0.989, P=0.03) were associated with a reduced risk of colorectal cancer (Figure 4). Scatter plots are provided in Figure S9. The funnel plot of SNP distributions was symmetrical, indicating no substantial quantitative bias (Figure S10). Apart from the result from the MR-Egger slope test for antihypertensive medications in colorectal cancer, the results were directionally consistent with the IVW method in all other supplementary methods. Notably, alpha-blockers showed no causal association with either gastric or colorectal cancer, while diuretics showed no relationship with gastric cancer (Table S14). Leave-one-out analysis confirmed the stability of the results (Figure S11). Moreover, MR-RAPS analyses demonstrated that the primary findings were reliable and robust to sample overlap, thereby providing support for the core assumptions of our MR analysis (Table S15).

Figure 4.

Figure 4

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Mendelian randomization results of causal effects between anti-hypertensive drugs and gastrointestinal cancer risk. ACEI/ARB, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker; CCB, calcium channel blocker; CI, confidence interval; IVW, inverse variance weighted; OR, odds ratio; SNP, single-nucleotide polymorphism.

Discussion

To our knowledge, this is the first MR study to systematically evaluate the causal relationship between hypertension and cancer risk. By leveraging GWAS data from multiple cancer types, our findings suggest that hypertension is causally associated with a decreased risk of gastric and colorectal cancer. Additionally, a weak reverse causal association was observed between lymphoma, thyroid cancer and hypertension. Further investigation revealed that the inverse relationship between hypertension and gastrointestinal cancer may be mediated by biological pathways that are also targeted by ACEI/ARB, beta-blockers, CCB, and diuretics.

Hypertension affects approximately 37% of the global adults and is one of the most common comorbidities among cancer patients (33). Given its widespread prevalence, any alteration in disease risk associated with hypertension could have significant public health implications. Our study reveals a significant causal association between hypertension and the decreased risk of gastric (OR =0.615, 95% CI: 0.415–0.912, P=0.02) and colorectal cancer (OR =0.708, 95% CI: 0.516–0.971, P=0.03). These findings are supported by a global study assessing risk factors for gastrointestinal cancers, which also identified an inverse relationship between hypertension and both gastric (OR =0.807, P=0.03) and colorectal cancer (OR =0.683, P=0.01) (16). However, a meta-analysis study found that hypertension was associated with an elevated risk of colorectal cancer (OR =1.15), although sensitivity analyses indicated substantial heterogeneity (34). The discrepancies across studies may stem from the inherent limitations of observational research, which is the primary approach for investigating the relationship between hypertension and cancer in real-world. Observational studies are susceptible to data inconsistencies, case misclassification, and small sample sizes. Additionally, since hypertension and cancer share common risk factors—such as smoking, alcohol consumption, and unhealthy dietary habits (35)—confounders inevitably influence results in traditional epidemiological studies, potentially leading to unreliable conclusions. In contrast, our study employs MR, which utilizes genetic variations as IVs to infer causality. This approach effectively mitigates biases arising from confounding factors and reverse causation, providing evidence analogous to randomized controlled trials (36). By investigating the association between hypertension and cancer at the genetic level, our study offers a more robust and reliable perspective on their causal relationship.

The reduced risk of gastrointestinal cancers associated with hypertension may be closely related to the biological pathways targeted by anti-hypertensive drugs. Our research shows that among anti-hypertensive medications, ACEI/ARB, beta-blockers, and CCB play a significant role in reducing the risk of gastrointestinal cancer. These medications may influence tumor initiation and progression through various mechanisms. ACEI/ARB has been found to inhibit angiogenesis in gastric cancer by reducing the expression of vascular endothelial growth factor A and matrix metalloproteinase-7 (37). Furthermore, the renin-angiotensin system (RAS) is involved in the regulation of the tumor microenvironment, and ACEI/ARB has been shown to block the immune-suppressive tumor microenvironment in colorectal cancer mediated by RAS (38). Beta-adrenergic receptors stimulate cancer cell proliferation and migration via cyclic adenosine monophosphate-dependent signaling pathways. Beta-blockers may inhibit tumor development by blocking this pathway (39). In addition, beta-blockers have been shown to reduce gastrointestinal inflammation and oxidative stress, providing protective effects against gastrointestinal cancers (40). CCB may induce apoptosis in tumor stem cells (41), while diuretics may inhibit tumor cell growth by regulating the expression of anti-apoptotic survival proteins (42). Several observational studies have also reported that ACEI/ARB (31,32), beta-blockers (43,44), and CCB (45,46) are associated with reduced risks of various cancers. Both laboratory research and epidemiological evidence further support the role of anti-hypertensive drugs in lowering the risk of gastrointestinal cancers. However, the potential for confounding by indication must be considered. The use of antihypertensive drugs may be protective, but it also serves as a marker of more severe hypertension and underlying comorbidities, both of which could independently affect cancer risk. Thus, although the biological mechanisms described above are plausible, the observed reduction in risk may reflect a mixture of genuine biological effects and confounding. Future studies using methods better suited to address this confounding, such as MR studies targeting specific drug targets or randomized controlled trials, are needed to validate these causal inferences.

Validation in an East Asian cohort revealed a significantly stronger inverse association between hypertension and gastric cancer (OR =0.573) than that reported in European populations (OR =0.615). This discrepancy may be attributed to distinct genetic susceptibilities to gastric cancer between these populations. For instance, East Asians exhibit higher allele frequencies in certain risk-related genes (such as PSCA and MUC1) (47,48), and the genetic background of hypertension may interact uniquely with these gastric cancer susceptibility loci, thereby contributing to the different effects observed.

The reverse MR analysis revealed a statistically significant but minimal inverse association between genetic liability to lymphoma and hypertension (OR =0.992, 95% CI: 0.985–1.000, P=0.04). Conversely, a significant yet weak positive association was observed between genetic predisposition to thyroid cancer and hypertension (OR =1.008, 95% CI: 1.002–1.013, P=0.01). However, the effect sizes for both associations are extremely close to the null value (OR =1.00) and are likely of limited clinical relevance. While these associations may suggest potential biological links, the exact underlying mechanisms remain unclear and warrant further investigation. The observed signals could also partly reflect biases such as residual pleiotropy or confounding. Thus, these results should be interpreted with caution.

There are several advantages in this study. First, we employed the MR method to explore the causal relationship between hypertension and cancer from a novel perspective, effectively eliminating common confounding factors present in epidemiological studies. Second, we implemented rigorous quality control and used multiple SNPs closely associated with hypertension. Third, we conducted several sensitivity analyses to verify the consistency of the causal relationship. We deliberately selected large GWAS summary statistics that were primarily based on individuals of European ancestry. These databases typically apply rigorous standardization and quality control procedures, which helps to minimize population stratification and technical batch effects across different studies. Finally, we used large, European-ancestry GWAS with strict quality control to curb stratification and batch effects; cross-database and cross-population replication confirm robustness.

There are still some limitations in this study. First, although we conducted several sensitivity analyses to minimize bias, it is impossible to completely eliminate all biases. Second, the use of publicly available summary statistics precluded access to individual-level data, preventing direct assessment of sample overlap or subtle population stratification. Third, although the validation in the FinnGen cohort was directionally consistent, it did not reach statistical significance. Forth, since we relied on publicly available summary statistics, we did not have access to individual-level data to directly test and quantify sample overlap or subtle population stratification. Finally, due to the absence of gender-specific GWAS summary statistics, we were unable to explore potential gender differences, despite the fact that the incidence of certain cancers exhibits gender specificity.

Conclusions

In conclusion, we employed MR analysis to comprehensively assess the causal relationship between hypertension and various cancers. Our findings suggested that genetic predisposition to hypertension was associated with a reduced risk of gastric and colorectal cancer. This inverse relationship may be mediated by biological pathways that are targeted by antihypertensive drugs, highlighting a potential mechanistic link worthy of further clinical investigation.

Supplementary

The article’s supplementary files as

tcr-14-11-7700-rc.pdf (337.6KB, pdf)
DOI: 10.21037/tcr-2025-1168
tcr-14-11-7700-coif.pdf (1.4MB, pdf)
DOI: 10.21037/tcr-2025-1168
tcr-14-11-7700-supplementary.pdf (2.6MB, pdf)
DOI: 10.21037/tcr-2025-1168

Acknowledgments

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

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.

Footnotes

Reporting Checklist: The authors have completed the STROBE-MR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1168/rc

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://tcr.amegroups.com/article/view/10.21037/tcr-2025-1168/coif). The authors have no conflicts of interest to declare.

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