Erectile dysfunction increases the risk of stroke: evidence from NHANES and Mendelian randomization analysis

Introduction

Erectile dysfunction (ED) is defined as the persistent or recurrent inability to achieve or maintain a penile erection sufficient for sexual activity (1), posing significant risks to both the physical and mental health of men. These patients frequently experience depression and social withdrawal, substantially impairing the quality of life of both themselves and their partners (2). In the United States, a cross-sectional analysis of 2,126 adult men from the 2001–2002 National Health and Nutrition Examination Survey (NHANES) reported an overall ED prevalence of 18.4% in men aged 20 years and older (3). By 2021, the prevalence had risen slightly, reaching 24.2% according to the National Survey of Sexual Wellbeing (4).

In addition to being a distressing condition, ED is recognized as a potential precursor of cardiovascular disease (CVD). Both ED and CVD are considered manifestations of a common physiologic phenomenon, with endothelial dysfunction as the underlying pathologic basis (5). Epidemiologic investigations have also identified shared risk factors for ED and CVD, including age, smoking, body mass index (BMI), total cholesterol, triglycerides, and diabetes mellitus (6). Despite these observations, evidence on the association between ED and CVD remains limited. A previously study has reported significant associations between ED and subsequent angina, myocardial infarction, and stroke (7). Several meta-analyses of cohort studies have confirmed that ED patients have a substantially increased risk of total CVD (8-10). In contrast, Speel et al. reported no significant association between ED and CVD in participants aged 40–50 and 60–70 years (11). Recently, Mendelian randomization (MR) has been utilized to investigate the relationship between CVD and ED, as it can mitigate the confounding factors. For example, Li et al. reported an elevated risk of ED among CVD patients based on MR analysis (12). Nevertheless, evidence from MR should be considered alongside findings from epidemiological studies, clinical trials, and basic science experiments (13).

Accumulating evidence indicates that ED may serve as an early marker of CVD. Previous research by Montorsi et al. demonstrated that nearly 70% of patients with angiographically confirmed coronary artery disease exhibited ED prior to the onset of angina, suggesting that ED is an early indicator of CVD (14). To investigate this association and explore its potential causal relationship, we combined observational analyses with genetic causal inference. Using NHANES data, we first examined the association between ED and CVD after adjusting for key covariates. Then we employed MR analyses, based on published genome-wide association study (GWAS) summary statistics, to elucidate the potential causal effect of ED on subsequent CVD risk. This integrated approach aims to provide robust evidence for the role of ED in the development of CVD and to provide a rationale for early prevention strategies in high-risk individuals. We present this article in accordance with the STROBE-MR reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-396/rc).

Methods

Study population in NHANES

NHANES (https://www.cdc.gov/nchs/nhanes) is a population-based cross-sectional survey designed to assess the health and nutritional status of the United States population. It collects data through standardized interviews, physical examinations, dietary assessments, and laboratory tests (15). For this study, only data from the 2001–2004 NHANES cycles were included, as other cycles lacked information on ED and CVD. Men aged 20 years and older were surveyed regarding ED, and participants younger than 20 or female were excluded. Therefore, all participants included in this analysis were adult men. CVD data were obtained from the Medical Health Questionnaire, which provides self-reported information on a wide range of health conditions. After applying inclusion and exclusion criteria, a total of 3,624 participants were selected from 21,161 eligible individuals. Figure 1 shows the participant selection process. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Figure 1 NHANES data screening flow chart. BMI, body mass index; MEC, Mobile Examination Center; NHANES, National Health and Nutrition Examination Survey.

Confirmation of ED and CVD in NHANES

ED was assessed using questionnaire item KIQ400—“Ability to maintain an erection”. Participants selected one of four responses: “always or almost always able to get and keep an erection”, “usually able”, “sometimes able”, or “never able”. These responses were used to classify ED into four categories: always/almost always able, usually able, sometimes able, and never able. CVD status was determined based on self-reported responses to the following question: “Has a doctor or other health professional ever told you had congestive heart failure (MCQ160B), coronary heart disease (MCQ160C), angina/angina pectoris (MCQ160D), heart attack (MCQ160E), or stroke (MCQ160F)?”.

Definition of covariates in NHANES

Covariates potentially associated with ED and CVD were selected from the NHANES 2001–2004 dataset, including age, race, education, citizenship, marital status, poverty index, physical activity, alcohol consumption, smoking, BMI, diastolic blood pressure (DBP), systolic blood pressure (SBP), congestive heart failure, angina, heart attack, and stroke. Physical activity was defined using PAQ180—“Average level of physical activity each day”: individuals reporting infrequent walking/lifting were classified as inactive, and those reporting frequent stair climbing, mountain climbing, or heavy work were classified as active. Alcohol consumption was defined as >12 alcoholic beverages in any year, with one beverage equivalent to 12 ounces of beer, 4 ounces of wine, or 1 ounce of liquor. Smoking is defined as having smoked at least 100 cigarettes in one’s life.

Data source for MR

ED data were obtained from the IEU open GWAS project (https://gwas.mrcieu.ac.uk/). The first dataset (GWAS ID: ebi-a-GCST006956; Exposure 1) included 6,175 cases and 217,630 controls and was used as the training dataset. ED was defined as self-reported or physician-diagnosed ED according to International Classification of Diseases (ICD) 10 codes N48.4 and F52.2, use of oral ED medication (sildenafil/Viagra, tadalafil/Cialis, or vardenafil/Levitra), or a history of surgical intervention for ED (OPCS-4 codes L97.1 and N32.6) (16). A second ED dataset from a Finnish cohort (GWAS ID: finn-b-ERECTILE_DYSFUNCTION; Exposure 2) included 1,154 cases and 94,024 controls and served as a validation dataset. ED in this dataset was identified from prescription records using the Anatomical Therapeutic Chemical (ATC) code G04BE.

Stroke data were obtained from the MEGASTROKE consortium (https://www.megastroke.org/), comprising 40,585 cases and 406,111 controls (17). The dataset included phenotypes for any stroke, any ischemic stroke, large artery stroke, cardioembolic stroke, and small vessel stroke. All datasets used in the MR analyses were of European ancestry. The MR analysis data are freely available in public databases, and the consortium data processing, including the study cohort, has received appropriate ethical approval. The research code used for data processing is also available (https://mrcieu.github.io/TwoSampleMR/articles/introduction.html).

Genetic instrument selection for ED

Genetic instrumental variables (IVs) for ED were derived from GWAS summary statistics. Valid IVs were required to satisfy three core assumptions (relevance, independence, and exclusion restriction): (I) IVs must be closely related to ED; (II) IVs must not be associated with any confounding variables that affect both ED and stroke; and (III) IVs should not affect stroke directly but only through ED. Single nucleotide polymorphisms (SNPs) with a threshold P<5×10⁻⁵ were initially selected. To ensure independence, SNPs in linkage disequilibrium (LD) were removed using an r² threshold of 0.001 and a clumping window of 10,000 kb. Instrument strength was evaluated using the F statistic, retaining SNPs with F>10 as strong instruments for ED (18). The F statistic is calculated using the following formula: F = (N − 2) × R²/(1 − R²) (19).

Statistical analysis

Baseline characteristics were summarized according to erection status to assess differences in socioeconomic factors, lifestyle behaviors, and physical measurement. Continuous variables were presented as mean ± standard deviation (SD) and compared using the Wilcoxon rank-sum test, whereas categorical variables were expressed as percentages and compared using the χ² test. Univariate logistics regression was used to determine the relationship between ED and CVD. Then three multivariate logistic regression models were constructed to further assess the association between ED and CVD after adjusting covariates: Model 1 included erection status, age, education, marital status, military service and poverty index; Model 2 additionally adjusted for smoking and physical activity; and Model 3 further adjusted for BMI, SBP and DBP. All results are expressed as odds ratio (OR) and 95% confidence interval (CI).

Two-sample MR was performed to estimate the relationship between ED and CVD. The inverse variance weighted (IVW) method was used as the primary estimator, supplemented by MR-Egger regression, and the weighted median. Sensitivity analyses included Cochran’s Q (to assess heterogeneity), the Egger intercept (to detect horizontal pleiotropy), and a leave-one-out (LOO) analysis (to evaluate the influence of individual SNPs). A two-sided P value <0.05 was considered statistically significant. In addition, inverse MR was used to verify the directionality of the causal relationship between ED and stroke. All the above analyses were completed in R software version 4.4.2, and the R packages used were survey, TwoSampleMR (version 0.6.8), and ggplot2.

Results

Baseline characteristics of NHANES study participants

A total of 3,624 males ≥20 years of age were obtained from the NHANES screening data (Table S1), representing a weighted population of 78,910,589.6 individuals. Their baseline characteristics are shown in Table S2. The participants who were always or almost always able, usually able, sometimes able, and never able were composed of 449,869,162.7 (63.20%), 14,505,655.3 (18.83%), 9,731,315.6 (12.33%), and 4,804,456.0 (6.09%), respectively. Among participants with different degrees of ED, we found that age, military status, education, marital status, poverty, BMI, SBP, DBP, Smoking, physical activity, congestive heart failure, angina, heart attack, and stroke had statistically significant differences (P<0.001).

NHANES revealed an increased risk of stroke in ED population

Regression results (Table 1) showed that, in univariate analyses, participants in the “sometimes able” and “never able” groups had significantly higher odds of all CVD outcomes (e.g., congestive heart failure, angina, heart attack and stroke) compared with those in the “always” or “almost always able” group (P<0.001). After adjustment in Model 1, participants in the “sometimes able” and “never able” groups had higher odds of congestive heart failure and stroke (P<0.05). Following adjustment in Model 2 and Model 3, only the “never able” group remained significantly associated with increased odds of stroke compared with the “always” or “almost always able” group [Model 2, OR (95% CI): 2.44 (1.17–5.10), P=0.03; Model 3, OR (95% CI): 2.42 (1.20–4.91), P=0.03]. No significant associations were observed between ED and congestive heart failure, angina, or heart attack in any model (P>0.05).

MR analysis confirmed increased risk of stroke among ED population

Given the observed association between ED and stroke in the NHANES study, we performed MR analysis to investigate the association from a genetic perspective. The results (Figure 2, Table S3) indicated that, in the training set (Exposure 1), ED was associated with increased odds of any stroke, any ischemic stroke, large artery stroke, and cardioembolic stroke. In the validation set (Exposure 2), ED was associated only with small vessel stroke. Combined analyses showed that ED was significantly associated with increased odds of large artery stroke (OR: 1.06; 95% CI: 1.00–1.11; P<0.05) and small vessel stroke (OR: 1.06; 95% CI: 1.04–1.09; P<0.001). For each one-SD increase in genetically predicted ED, the odds of large artery stroke and small vessel stroke increased by 6%. The scatterplot trend was consistent with these findings (Figure 3), and the funnel plot indicated a uniform distribution of points, suggesting no evidence of pleiotropy (Figure 4). Cochran’s Q and Egger intercept tests also showed no heterogeneity or horizontal pleiotropy, and all F-statistics exceeded 10 (Table S4). LOO analysis for Exposure 1 and any stroke indicated that several SNPs had a substantial influence on the outcome, suggesting some instability in these results (Figure 5).

Figure 2 Forest plot of MR results. Exposure 1, the first dataset (GWAS ID: ebi-a-GCST006956); Exposure 2, the second dataset (GWAS ID: finn-b-ERECTILE_DYSFUNCTION). CI, confidence interval; IV, instrumental variable; MR, Mendelian randomization; OR, odds ratio.

Figure 3 Scatter plot. Analysis of the results of Exposure 1 (A-E) and Exposure 2 (F-J) on the outcomes of any stroke (A,F), any ischemic stroke (B,G), large artery stroke (C,H), cardioembolic stroke (D,I), and small vessel stroke (E,J). Exposure 1, the first dataset (GWAS ID: ebi-a-GCST006956); Exposure 2, the second dataset (GWAS ID: finn-b-ERECTILE_DYSFUNCTION). MR, Mendelian randomization; SNP, single nucleotide polymorphism.

Figure 4 Funnel plot. Pleiotropy analysis of instrumental variables related to Exposure 1 (A-E) and Exposure 2 (F-J) and outcomes any stroke (A,F), any ischemic stroke (B,G), large artery stroke (C,H), cardioembolic stroke (D,I), small vessel stroke (E,J). Exposure 1, the first dataset (GWAS ID: ebi-a-GCST006956); Exposure 2, the second dataset (GWAS ID: finn-b-ERECTILE_DYSFUNCTION). IV, instrumental variable; MR, Mendelian randomization; SE, standard error.

Figure 5 LOO method to test whether there is a specific instrumental variable that affects the outcome by testing the instrumental variables related to Exposure 1 and Exposure 2 and outcomes any stroke (A,F), any ischemic stroke (B,G), large artery stroke (C,H), cardioembolic stroke (D,I), small vessel stroke (E,J). Exposure 1, the first dataset (GWAS ID: ebi-a-GCST006956); Exposure 2, the second dataset (GWAS ID: finn-b-ERECTILE_DYSFUNCTION). LOO, leave-one-out.

Among the reverse MR results, only cardioembolic stroke (OR: 1.05, 95% CI: 1.00–1.10, P=0.03) and small vessel stroke (OR: 0.96, 95% CI: 0.92–1.00, P=0.03) showed an effect on Exposure 2 (Figure S1, Table S5). The F-statistics for the selected IVs were >10 (Table S6), and there was no heterogeneity or pleiotropy (Figures S2,S3). However, the LOO results (Figure S4) indicated the presence of specific SNPs, and the estimated causal relationship was primarily dependent on these SNPs. The final IVW results were unstable, and the MR-Egger and weighted median results also did not support a causal relationship. Furthermore, the integration of the results from Exposure 1 and Exposure 2 indicated that stroke may not cause ED, further confirming the directionality that ED may increase the risk of stroke.

Discussion

ED is not only a common male sexual disorder but also increasingly recognized as a potential marker of systemic vascular disease, sharing pathophysiological mechanisms with cardiovascular events such as stroke (20). Our findings indicate that ED may contribute to an increased risk of stroke. In the observational NHANES analysis, ED was associated with higher odds of congestive heart failure, angina, heart attack, and stroke in univariate analysis. However, after adjusting for covariates, only the association with stroke remained significant. Subsequent MR analysis focusing on stroke subtypes suggested a potential causal effect of ED on large artery stroke and small vessel stroke. Together, the NHANES and MR results provide convergent evidence that ED is linked to an elevated risk of stroke.

Although ED and CVD share common pathophysiological mechanisms, there is limited consensus on whether ED increases the risk of CVD. In a large meta-analysis of 12 prospective cohort studies, men with ED had an increased risk of CVD, including coronary heart disease, stroke, and all-cause mortality (10). A prospective case-cohort study found that men with ED were more likely to have a stroke than controls during a 5-year follow-up [risk ratio (RR) =1.29, 95% CI: 1.08–1.54, P<0.01] (21). During a 15-year follow-up of 1,209 men, after adjusting for age and other cardiovascular risk factors, men with ED had a 150% increased risk of stroke during the 15-year period, indicating that ED is an independent risk factor for stroke (22). However, other studies have failed to demonstrate an independent association between ED and CVD or stroke. Ponholzer et al. did not show a statistically significant association between ED and CV events in a cohort of 2,506 men aged 20–80 years (23). There was a statistically significant association between ED incidence and subsequent coronary heart disease (P=0.04), whereas the risk of stroke was only suggestive (P=0.06) (10). In our observational study, men with ED who were never able to have an erection had a 142% increased risk of stroke, which was 2.42 times that of those without ED. The higher percentage in our study may be due to the fact that we categorized men according to the degree of ED, and the percentage may decrease if mild or moderate ED was included.

In our study, NHANES-based analysis revealed that men categorized as “sometimes able” or “never able” to achieve an erection had significantly higher odds of all four CVD outcomes in univariate analyses, before adjusting for covariates. After adjustment for covariates, only the association between “never able” to get an erection and stroke was stable. In the MR analysis, we further explored the causal link between ED and various stroke subtypes using two independent GWAS datasets, minimizing bias from population differences.

Our results supported an association between ED and an increased risk of certain stroke subtypes, particularly large artery stroke and small vessel stroke. This suggests that ED may exert a significant effect on specific types of stroke, while its impact on other subtypes appears weak or insignificant. In the MR analysis, each SD increase in genetically predicted ED risk was associated with a 6% higher incidence of large artery stroke and small vessel stroke (OR =1.06). Although the effect size is modest at the individual level, the high prevalence of both ED and stroke among older men indicates that this relationship could have substantial public health implications.

The validity of our MR findings rests on the core assumptions of relevance, independence, and exclusion restriction. All selected SNPs were strongly associated with ED (F-statistics >10), supporting the relevance assumption. Independence was addressed by using non-overlapping GWAS datasets and excluding SNPs associated with known confounders. The exclusion restriction assumption was supported by the absence of horizontal pleiotropy, as indicated by symmetrical funnel plots and non-significant MR-Egger intercepts and Cochran’s Q statistics. Nonetheless, residual pleiotropy cannot be entirely excluded and remains an inherent limitation of MR analyses. Sensitivity analyses further reinforced the robustness of our findings. LOO analysis revealed some instability in the association between genetically predicted ED and any stroke, which was a non-significant outcome in our study. This suggests that the null association observed for any stroke may have been influenced by a small number of SNPs and should be interpreted with caution. Importantly, no such instability was observed for large artery stroke or small vessel stroke, indicating that these significant associations are robust and not driven by individual variants. Biologically, ED and stroke share common vascular mechanisms, such as endothelial dysfunction and atherosclerosis, supporting the plausibility of a directional causal effect from ED to stroke. Moreover, the lack of consistent evidence for reverse causality further strengthens this inference.

The exact mechanism by which ED leads to stroke is not yet clear, but there are some possible explanations. Nitric oxide (NO) plays an important role in the normal physiological process of penile erection. Sexual impulse induces the production of parasympathetic NO and other endothelial mediators, which promote relaxation of smooth muscle in the penile arteries and increase blood flow to the penis while blocking venous outflow (24). These processes cause blood to be retained in the corpus cavernosum, thereby inducing penile erection (25). It is now believed that most cases of ED are caused by physical organic causes, usually due to underlying vascular causes. In ED, dysfunctional endothelial cells affect acetylcholine (ACh) release, resulting in altered NO production (26). Free radical damage and the availability of NO also lead to increased aggregation of platelets and neutrophils and the release of vasoconstrictor substances (27). NO response is limited and sticky factors accumulate, which reduces the relaxation of vascular smooth muscle, leading to ED (28). The same mechanism also occurs in the formation of atherosclerotic plaques and endothelial dysfunction in the brain, which is a fundamental risk factor for stroke (29). Notably, the penile arteries are smaller (1–2 mm) compared with the major cerebral arteries (2–5 mm), meaning that the same degree of endothelial dysfunction and atherosclerosis can result in a greater reduction in blood flow and decreased vascular resilience in the erectile tissue relative to cerebral vessels (30,31). Therefore, the penis, as a vascular organ, may be very sensitive to endothelial dysfunction and changes in systemic NO levels (32). Over time, these systemic dysfunctions can lead to the development of chronic CVD or stroke. Further research is needed to explore the potential mechanisms by which ED causes stroke.

There are some limitations of our study. First, in the analysis of NHANES data, whether the population taking drugs for the treatment of prostate cancer and other diseases in the questionnaire survey on ED was not excluded. Second, ED in the NHANES cohort was assessed via self-reported questionnaire rather than standardized instruments such as the International Index of Erectile Function (IIEF or IIEF-5), which may introduce subjectivity and reduce diagnostic precision. Although self-reported sexual function has been considered generally reliable, response bias cannot be ruled out, as participants may misunderstand questions or intentionally underreport symptoms due to privacy concerns. Third, in the MR analysis, the two genetic exposure datasets used different definitions of ED (e.g., clinical diagnosis, medication use, or ICD codes), which may introduce heterogeneity. This inconsistency in phenotype definition could influence the comparability and interpretation of MR results and should be considered when evaluating causal estimates. In addition, all GWAS participants were of European ancestry, and recruitment criteria largely focused on population-based or hospital-based cohorts with standardized diagnostic definitions. We acknowledge that minor differences in population structure and recruitment settings across cohorts may still exist, which could potentially bias MR estimates through residual population stratification.

Conclusions

In summary, we investigated the risk of CVD among the ED population based on the combination of NHANES database and MR analysis. NHANES data showed that never able to get and keep an erection was associated with stroke. In MR analysis, genetically predicted ED was causally associated with a higher risk of large artery stroke and small vessel stroke.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE-MR reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-396/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-396/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-396/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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