The causal effect of family history of cardiovascular disease on erectile dysfunction: a randomized clinical study and Mendelian randomization study

Abstract

Erectile dysfunction (ED) is increasingly recognized as an early clinical marker of cardiovascular disease (CVD); however, the causal role of familial predisposition to CVD in ED development remains insufficiently defined. This study investigated whether genetic susceptibility associated with a parental history of CVD exerts a causal influence on ED risk, integrating clinical data with Mendelian randomization (MR) analysis. A cohort of 288 men who attended the Department of Andrology of Xiangya Hospital (Changsha, China) between June 2017 and June 2023 were recruited, comprising 223 patients with clinically confirmed ED and 65 controls. Detailed demographic, cardiovascular, and ED severity data were collected. Genetic variants associated with ED and parental CVD history were obtained from genome-wide association study (GWAS) summary statistics, and two-sample MR analyses were conducted to evaluate causal effects. Clinically, men with ED were significantly older, exhibited higher body mass index (BMI), and demonstrated lower testosterone levels compared with controls. A trend toward an association between family history of CVD and ED was observed. MR analyses provided robust evidence of causality, with paternal CVD history increasing ED risk and maternal CVD history exerting an even stronger effect. Sensitivity analyses confirmed the stability of these findings without evidence of pleiotropic bias. Collectively, these results indicate that familial genetic susceptibility to CVD independently contributes to the risk of ED. These findings underscore the clinical importance of incorporating family history into ED risk stratification and highlight the need for early screening and preventive strategies in men with a family history of CVD. Proactive management of this high-risk population may mitigate the future burden of ED and its cardiovascular sequelae.

INTRODUCTION

Erectile dysfunction (ED), defined as the persistent inability to achieve or maintain a penile erection sufficient for satisfactory sexual performance, has emerged as a major global health concern.1 Epidemiological projections estimate that by 2025, more than 320 million men worldwide will be affected,2 underscoring its significance as one of the most prevalent male sexual disorders. The pathogenesis of ED is multifactorial, involving complex interactions among neurogenic, vascular, endocrine, and psychological determinants.3 Increasingly, ED is recognized not merely as a quality-of-life disorder but as an important clinical marker of systemic disease. In particular, a robust body of evidence demonstrates its strong association with cardiovascular morbidity, with longitudinal studies confirming its predictive value for future major adverse cardiovascular events (MACE).

The risk of cardiovascular disease (CVD) appears to rise in parallel with increasing ED severity,4 a relationship largely explained by their shared pathophysiological substrate: endothelial dysfunction.5 Beyond this, emerging data highlight the role of familial predisposition. A positive family history (FH) of cardiometabolic disorders not only reflects inherited metabolic and vascular risk but also serves as a prognostic indicator for MACE.6 Nevertheless, the potential predictive utility of FH of CVD (FH-CVD) in the development and progression of ED has received little attention, and the specific epidemiological links between these conditions remain underexplored. To address this knowledge gap, we conducted a case–control study enrolling a rigorously phenotyped cohort of ED patients and healthy controls. Through standardized, structured interviews, we systematically documented multigenerational CVD family histories to assess the transgenerational influence of cardiovascular predisposition on ED manifestation.

Mendelian randomization (MR) offers a powerful epidemiological framework for testing causal hypotheses by leveraging genetic variants as instrumental variables.7 Because these variants are randomly assorted during gamete formation and largely independent of environmental or behavioral influences, MR analyses are less susceptible to confounding and reverse causation, and are therefore often regarded as comparable in inferential strength to randomized controlled trial.8

In this study, we adopted a triangulated analytic strategy integrating three complementary approaches: (1) prospective clinical phenotyping of our ED cohort, (2) systematic assessment of FH using validated instruments, and (3) bidirectional two-sample MR analyses employing genome-wide association study (GWAS) summary statistics. This multimodal framework was designed to provide a robust interrogation of the potential causal relationship between transgenerational cardiovascular risk transmission and ED pathogenesis.

PARTICIPANTS AND METHODS

Study participants and ethical approval

This cross-sectional study enrolled a consecutive cohort of 288 male patients who attended the Department of Andrology of Xiangya Hospital (Changsha, China) between June 2017 and June 2023. Participants were excluded if they declined to provide information, failed to complete the study questionnaire, or had a history of mental illness. The ED group comprised men with clinically confirmed ED of at least six months’ duration, whereas the control group included age-matched men presenting with non-ED sexual complaints or attending routine health examinations. Written informed consent was obtained from all participants prior to enrollment. The study protocol has been reviewed and approved by the Institutional Review Board of Xiangya Hospital (Approval No. 2019-S252), with concurrent approval for the disclosure of relevant data involved in this study.

Questionnaire assessments

Before diagnosis or treatment, all participants completed detailed questionnaires that collected demographic characteristics, personal history of CVD, and FH-CVD. FH-CVD was determined using a structured questionnaire in which participants reported parental diagnoses of hypertension, coronary heart disease, arrhythmia, or other cardiovascular conditions. A positive FH was defined as the presence of at least one such diagnosis in either parent. Erectile function was assessed using the International Index of Erectile Function-5 (IIEF-5), a validated instrument.9 Scores were categorized as follows: no ED (22–25), mild ED (16–21), mild-to-moderate ED (12–15), and moderate-to-severe ED (5–11).

To further characterize psychosocial factors, participants also completed lifestyle questionnaires along with the Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9).10 The GAD-7 consists of seven items scored on a four-point scale (0–3), yielding a total score of 0 to 21, with higher scores reflecting greater levels of anxiety. Similarly, the PHQ-9 includes nine items scored on a similar scale, resulting in a total score of 0 to 27, with higher scores reflecting more severe depressive symptoms.

Physical examinations and laboratory assessments

All participants underwent standardized physical examinations and laboratory assessments. Physical measures included body weight, height, blood pressure, pulse rate, respiratory rate, and daily sedentary behavior. Body mass index (BMI) was calculated as weight divided by height squared (kg m⁻²). Medical histories were reviewed for the presence of diabetes mellitus, hypertension, and hyperlipidemia. Laboratory analyses included assessments of liver function, vitamin D level, and sex hormone-binding globulin (SHBG). All laboratory tests were performed in a blinded fashion, with technicians unaware of participants’ clinical status or study group assignment.

Genetic data sources

Genetic instruments for ED were derived from the UK Biobank, comprising 6175 cases and 217 630 controls.11 Instruments for CVD FH, including both paternal and maternal histories of heart disease, were derived from a separate UK Biobank dataset comprising 314 278 participants, of whom 27 696 reported maternal CVD and 14 338 reported paternal CVD.12 All participants included in these GWAS datasets were of European ancestry. A detailed summary of the GWAS sources used in this study is presented in Table 1. All datasets were publicly available through the GWAS catalog (https://gwas.mrcieu.ac.uk/; lasted accessed on 10 November 2024) and were employed for MR analyses.

Table 1.

Instrumental single-nucleotide polymorphism used for Mendelian randomization analyses of parental cardiovascular disease and erectile dysfunction

SNP	Chromosome	Position	EA	NEA	β	EAF	SE	P
Illnesses of mother heart disease
rs1047891	2	211540507	A	C	−0.00540965	0.315901	0.000931152	6.3×10−9
rs117733303	6	160922870	G	A	0.0371161	0.018444	0.00321717	8.6×10−31
rs1333047	9	22124504	T	A	0.0088187	0.493686	0.000866198	2.4×10−24
rs2071475	6	32782387	A	G	0.00598456	0.209023	0.00106458	1.9×10−8
rs4299376	2	44072576	T	G	−0.00517901	0.676891	0.000926436	2.3×10−8
rs72807674	2	25333105	C	A	0.00541094	0.300239	0.000948836	1.2×10−8
rs74617384	6	160997118	T	A	0.0210184	0.078865	0.00160689	4.3×10−39
rs8043119	15	79061002	A	G	−0.00515119	0.42772	0.000877644	4.4×10−9
rs9349379	6	12903957	G	A	0.00496304	0.405606	0.000881972	1.8×10−8
Illnesses of father heart disease
rs10416028	19	17850284	A	G	0.00742775	0.216865	0.00125998	3.7×10−9
rs10738607	9	22088094	G	A	0.0165908	0.489197	0.00103738	1.4×10−57
rs10774625	12	111910219	G	A	−0.00815792	0.503834	0.00103762	3.8×10−15
rs1125128	2	145837441	G	A	−0.00610719	0.63753	0.00107953	1.5×10−8
rs11556924	7	129663496	T	C	−0.00595608	0.388741	0.0010651	2.2×10−8
rs115600411	2	204121145	G	C	0.00877177	0.129235	0.00154582	1.4×10−8
rs11591147	1	55505647	T	G	−0.0243457	0.017431	0.00396351	8.1×10−10
rs117733303	6	160922870	G	A	0.0420666	0.0185	0.0038482	8.1×10−28
rs117779442	8	19839709	T	C	−0.0113002	0.074679	0.00198054	1.2×10−8
rs141622900	19	45426792	A	G	−0.0149706	0.05242	0.00238525	3.5×10−10
rs15052	19	41813375	C	T	0.00853317	0.176245	0.00136632	4.2×10−10
rs1878406	4	148393664	T	C	0.00888744	0.140778	0.00149105	2.5×10−9
rs216215	17	2140668	C	T	−0.00734206	0.278167	0.00115806	2.3×10−10
rs2519093	9	136141870	T	C	0.00820289	0.184972	0.00133623	8.3×10−10
rs2521501	15	91437388	T	A	0.00793234	0.322233	0.00111894	1.3×10−12
rs28929474	14	94844947	T	C	−0.0290107	0.019755	0.00373201	7.6×10−15
rs3127580	6	160710851	T	C	0.0114959	0.155524	0.00143126	9.6×10−16
rs4299376	2	44072576	T	G	−0.00641203	0.676588	0.00110952	7.5×10−9
rs55730499	6	161005610	T	C	0.0349501	0.079898	0.00191715	3.0×10−74
rs583104	1	109821307	T	G	0.00953428	0.773274	0.00123842	1.4×10−14
rs61826467	1	222941700	T	G	0.00827412	0.74843	0.00119884	5.1×10−12
rs62012628	15	79070000	T	C	0.00696561	0.286617	0.00115686	1.7×10−9
rs6511720	19	11202306	T	G	−0.0181574	0.118877	0.00160484	1.1×10−29
rs7475853	10	104673097	A	G	−0.0109787	0.077357	0.00194169	1.6×10−8
rs7500448	16	83045790	G	A	−0.00772396	0.253355	0.00120277	1.3×10−10
rs7719589	5	163748773	C	G	0.00753446	0.180235	0.00134926	2.3×10−8
rs9349379	6	12903957	G	A	0.00947957	0.40584	0.00105662	2.9×10−19
rs9515203	13	111049623	C	T	−0.00657441	0.262451	0.00117913	2.5×10−8
rs9980618	21	35600505	T	C	0.00969784	0.129996	0.00154663	3.6×10−10

SNP: single-nucleotide polymorphism; EA: effect allele; NEA: non-effect allele; EAF: effect allele frequency; SE: standard error; β: the magnitude of the association effect between genetic variation and exposure factors or outcome factors; -: a negative correlation between the genetic variation and the exposure or outcome factor

Instrumental variables (IVs) selection and statistical analyses

IVs were selected according to rigorous quality-control criteria. Independent single-nucleotide polymorphisms (SNPs) associated with ED or FH-CVD were retained if they met the genome-wide significance threshold (P < 5 × 10⁻⁸), had no evidence of linkage disequilibrium (LD, R² < 0.001), and were located at least 10 000 kb from index variants.13 Instrument strength was quantified using the F-statistic, calculated as F = R² × (N − 2)/(1 − R²). An F-statistic >10 was considered indicative of a sufficiently strong instrument to minimize weak-instrument bias. Here, R² represents the proportion of variance in the exposure explained by each SNP. For exposures with <10 SNP, R² was estimated using the formula: R² = 2 × EAF × (1 − EAF) × β². For exposures with ≥10 SNPs, R² was estimated using the formula: R² = (2 × β² × [1 − EAF] × EAF)/(2 × β² × [1 − EAF] × EAF + 2 × SE² × N × [1 − EAF] × EAF),14 where N denotes the sample size, β denotes the genetic effect size of the SNP on exposure, EAF denotes the effect allele frequency, and SE denotes the standard error. P < 0.05 was considered statistically significant.

RESULTS

Comparison of characteristics of patients with and without ED

Of the 288 men enrolled, 223 (77.4%) were diagnosed with ED. Table 2 summarizes the associations between sociodemographic, clinical, and biochemical parameters and ED status. Men with ED were significantly older than controls without ED (P < 0.001). Furthermore, ED patients exhibited higher BMI values (P = 0.004), suggesting a potential link between adiposity and vascular impairment. Serum testosterone levels demonstrated a clear downward trend in the ED group, approaching statistical significance (P = 0.060). By contrast, no statistically significant differences were detected among the groups in terms of fasting glucose, lipid profiles (total cholesterol, triglycerides, high-density lipoprotein [HDL], and low-density lipoprotein [LDL]), reproductive hormones (follicle-stimulating hormone [FSH], luteinizing hormone [LH], and prolactin [PRL]), or psychological assessment scores derived from the PHQ-9 and GAD-7 scales (all P > 0.05).

Table 2.

Association between baseline characteristics and erectile dysfunction

Characteristic	Without ED (mean±s.d.)	With ED (mean±s.d.)	Reference	P
Age (year)	30.1±7.0	34.8±8.7	None	<0.001**
BMI (kg m−2)	25.51±4.45	26.94±3.16	None	0.004*
Blood sugar (mmol l−1)	5.38±0.65	5.77±1.61	3.90–6.10	0.155
Cholesterol (mmol l−1)	5.00±0.90	4.98±1.05	2.80–5.17	0.944
Triglyceride (mmol l−1)	1.69±1.73	2.21±3.74	0.56–1.70	0.421
HDL (mmol l−1)	1.26±0.27	1.18±0.30	1.08–1.91	0.182
LDL (mmol l−1)	3.21±0.68	3.20±0.68	2.07–3.37	0.942
FSH (U l−1)	4.38±2.05	3.97±2.33	0.95–11.95	0.340
LH (U l−1)	4.65±1.66	4.54±2.11	1.24–8.62	0.785
Prolactin (ng ml−1)	13.04±6.76	11.45±7.63	1.61–18.77	0.266
Testosterone (nmol l−1)	20.82±6.88	18.17±7.44	9.45–37.45	0.060
PHQ-9	6.30±4.71	6.37±5.25	None	0.926
GAD-7	5.48±4.29	5.17±4.41	None	0.616

^*P<0.05; ^**P<0.001. s.d.: standard deviation; BMI: body mass index; HDL: high-density lipoprotein; LDL: low-density lipoprotein; FSH: follicle-stimulating hormone; LH: luteinizing hormone; PHQ: Patient Health Questionnaire; GAD: Generalized Anxiety Disorder; ED: erectile dysfunction

Comparison of clinical characteristics by FH-CVD

Table 3 presents the associations between participant characteristics and FH-CVD. Men with an FH-CVD demonstrated significantly higher BMI values compared with those without FH-CVD (mean: 27.07 kg m⁻² vs 25.85 kg m⁻²; P = 0.004). HDL cholesterol levels were markedly lower in the FH-CVD group compared with those without FH-CVD (mean: 1.13 mmol l⁻¹ vs 1.28 mmol l⁻¹; P = 0.005). In addition, FSH concentrations were significantly elevated among participants with FH-CVD (P = 0.029). While IIEF-5 scores did not differ significantly between groups, a trend toward lower scores was evident in participants with FH-CVD (15.04 vs 16.23; P = 0.094), as illustrated in Figure 1. Psychological assessment revealed no significant differences in anxiety (GAD-7; P = 0.867) or depressive symptoms (PHQ-9; P = 0.599) between groups.

Table 3.

Association between baseline characteristics and family history of cardiovascular disease

Characteristic	Without F H-CVD	With FH -CV D	Reference	P
Age (year)	32.9±8.1	35.00±9.4	None	0.045*
BMI (kg m−2)	25.85±3.96	27.07±3.38	None	0.004*
Blood sugar (mmol l−1)	5.46±0.55	5.84±1.93	3.90–6.10	0.120
Cholesterol (mmol l−1)	4.86±0.97	5.10±1.03	2.80–5.17	0.179
Triglyceride (mmol l−1)	2.08±4.26	2.01±1.74	0.56–1.70	0.902
HDL (mmol l−1)	1.28±0.35	1.13±0.21	1.08–1.91	0.005*
LDL (mmol l−1)	3.12±0.61	3.27±0.74	2.07–3.37	0.210
FSH (U l−1)	3.66±1.44	4.50±2.86	0.95–11.95	0.029*
LH (U l−1)	4.50±1.74	4.66±2.22	1.24–8.62	0.638
Prolactin (ng ml−1)	12.18±8.10	11.89±6.69	1.61–18.77	0.824
Testosterone (nmol l−1)	19.43±7.40	18.34±7.24	9.45–37.45	0.390

^*P<0.05. BMI: body mass index; CVD: cardiovascular disease; HDL: high-density lipoprotein; LDL: low-density lipoprotein; FSH: follicle-stimulating hormone; LH: luteinizing hormone; FH: family history

Figure 1.

Comparison of IIEF-5 between without FH-CVD and with FH-CVD groups. FH: family history; CVD: cardiovascular diseases; IIEF-5: International Index of Erectile Function-5.

IV selection

Rigorous quality-control criteria were applied, including genome-wide significance (P < 5 × 10⁻⁸), linkage disequilibrium thresholds (R² < 0.001 with a distance <10 000 kb), and instrument strength (F > 10). After harmonizing across datasets, 29 SNPs were retained as IVs to evaluate the causal effect of paternal cardiovascular disease on ED. Similarly, 9 SNPs were selected as IVs for maternal cardiovascular disease (Table 1).

Univariate Mendelian randomization (UVMR) analyses

UVMR analyses demonstrated a significant causal association between parental CVD and ED. Specifically, paternal cardiovascular disease was associated with increased ED risk (inverse-variance weighted [IVW] odds ratio [OR]: 3.20, 95% confidence interval [CI]: 1.11–9.25, P = 0.031), and maternal cardiovascular disease exhibited an even stronger effect (IVW OR: 7.90, 95% CI: 1.09–57.07, P = 0.040). Weighted median (WM) sensitivity analyses yielded consistent results for paternal disease (IVW OR: 3.72, 95% CI: 1.11–12.53, P = 0.033) and maternal disease (IVW OR: 15.58, 95% CI: 1.27–188.86, P = 0.031). By contrast, alternative approaches including MR-Egger regression, simple mode, and weighted mode analyses did not identify significant associations between parental CVD and ED (all P > 0.05; Supplementary Table 1).

Supplementary Table 1.

Causal effect of parental cardiovascular disease on erectile dysfunction estimated by Mendelian randomization analyses

Exposure	Outcome	n (SNP)	Method	OR	P
Mother heart disease	ED	8	MR-Egger	17.19	0.14
Mother heart disease	ED	8	Weighted median	15.58	0.03*
Mother heart disease	ED	8	Inverse variance weighted	7.90	0.04*
Mother heart disease	ED	8	Simple mode	17.72	0.16
Mother heart disease	ED	8	Weighted mode	19.55	0.06
Father heart disease	ED	29	MR-Egger	2.89	0.37
Father heart disease	ED	29	Weighted median	3.72	0.03*
Father heart disease	ED	29	Inverse variance weighted	3.20	0.03*
Father heart disease	ED	29	Simple mode	2.83	0.32
Father heart disease	ED	29	Weighted mode	3.77	0.07

^*P<0.05. ED: erectile dysfunction; OR: odds ratio; SNP: single-nucleotide polymorphism; MR: Mendelian randomization

Sensitivity and pleiotropy analyses

Forest plots and scatter plots depict the causal relationships between genetically predicted parental CVD and ED, including subtypes (Figure 2 and 3). Leave-one-out analyses confirmed that no single SNP disproportionately influenced the overall causal estimates, supporting the robustness of our findings. MR-Egger regression was additionally employed to detect outliers, but none were identified (Supplementary Table 2). Horizontal pleiotropy was formally evaluated using MR-Egger regression (P = 0.21), with no evidence of directional pleiotropy detected. Funnel plots further demonstrated a symmetric distribution of SNP effects on ED, providing additional evidence against substantial pleiotropic bias (Figure 2).

Figure 2.

Scatter plots of MR estimates. (a) MR estimates of genetic risk of father heart disease on ED. (b) MR estimates of genetic risk of mother heart disease on ED. ED: erectile dysfunction; SNP: single-nucleotide polymorphism; MR: Mendelian randomization; β: the magnitude of the association effect between genetic variation and exposure factors or outcome factors; SEIV: standard error of the instrumental variable estimate; ID: identifier.

Figure 3.

MR effect size. (a) Forest plots describe the effect size of each SNP of father heart disease on ED. (b) Forest plots describe the effect size of each SNP of mother heart disease on ED. ED: erectile dysfunction; IVW: inverse-variant weighted; SNP: single-nucleotide polymorphism; MR: Mendelian randomization; ID: identifier.

Supplementary Table 2.

Results of heterogeneity and pleiotropy for parental cardiovascular disease exposures

Exposure	MR-Egger intercept	Q-df value by IVW	Q-df value by MR-Egger
Mother heart disease	−0.079797*	7*	6*
Father heart disease	−0.000468*	28*	27*

^*P>0.05 (If P < 0.05, it indicates that certain SNPs may directly affect the outcomes). MR: Mendelian randomization; IVW: inverse-variance weighted

DISCUSSION

ED is conventionally categorized into three major types: organic, psychogenic, and mixed.15 Among these, mixed ED is the predominant subtype, representing the majority of cases.16 Importantly, ED and CVD share overlapping risk factors and common pathophysiological pathways, including endothelial dysfunction, smooth muscle cell impairment, and cavernosal artery pathology.17 The artery size hypothesis provides a further explanatory framework, positing that atherosclerosis disproportionately affects smaller arteries, such as the penile vasculature, before involving larger vessels. This model supports the view that ED and CVD represent distinct clinical manifestations of a shared underlying vascular pathology.18

In this study, we demonstrated that a positive FH-CVD is significantly associated with increased ED risk in a Chinese male population, thereby serving as a clinically meaningful predictor of future ED development. Although dichotomous classification of FH does not capture nuances such as disease severity or the number of affected relatives, it nonetheless provides a pragmatic and clinically applicable tool for risk stratification, particularly in younger men. Our findings revealed a dose-dependent relationship between the number of familial risk factors and adverse clinical features of ED, including elevated waist circumference, reduced HDL cholesterol, and increased blood glucose. Together, these data underscore a strong association between parental CVD history and ED onset. The MR analysis further substantiated these observations, demonstrating a causal relationship between both paternal and maternal CVD histories and the incidence of ED.

The evidence presented here indicates that an FH-CVD in first-degree relatives is associated with more severe vascular impairment and an elevated overall risk profile for ED, reinforcing its role as a predictive marker for disease development. Prior research has largely centered on familial CVD history as a predictor of subsequent cardiovascular events in offspring, such as myocardial infarction or heart failure. The present study extends this research direction by identifying the contribution of familial CVD history to ED risk. To our knowledge, this is one of the exploratory studies to directly evaluate the relationship between familial CVD and ED, thereby offering novel insights into an underexplored domain of cardiovascular and sexual health research.

Our prior work has emphasized the contribution of cardiovascular injury to ED pathogenesis, findings that align with the broader literature linking ED prevalence with CVD.19 Both conditions share well-established risk factors and mechanisms, including endothelial dysfunction, systemic inflammation, and reduced circulating testosterone levels.20 Beyond these mechanistic overlaps, ED has been increasingly recognized as an early and independent predictor of adverse cardiovascular outcomes, creating a critical opportunity for timely intervention and preventive strategies.21 Consistent with this framework, our MR analysis supports a causal genetic link between FH-CVD and ED risk, a result corroborated by the parallel findings of our clinical cohort study.

Multiple meta-analyses have established ED as a robust and independent predictor of CVD events, with affected individuals exhibiting a substantially elevated risk of future cardiovascular morbidity.4,22 The artery size hypothesis provides a compelling mechanistic explanation, suggesting that systemic atherosclerosis initially compromises smaller vessels, such as the penile arteries, before involving larger coronary or cerebral vessels. Consequently, ED frequently precedes the onset of overt CVD, serving as an early clinical marker of incipient vascular disease.13 Both ED and CVD are underpinned by shared etiological processes, including endothelial dysfunction, chronic inflammation, and metabolic disturbances. Individuals with an FH-CVD appear particularly vulnerable to these pathophysiological insults, underscoring the value of FH as a predictive marker for both CVD and ED. This convergence of risk highlights the critical importance of early identification and intervention in genetically susceptible populations.

The biological mechanisms linking familial CVD predisposition with ED risk remain incompletely elucidated. In our cohort, men with an FH-CVD demonstrated higher BMI and lower HDL cholesterol levels compared with those without such a history. These findings are consistent with prior studies indicating that obesity, particularly in older adults, is strongly associated with clustering of cardiometabolic risk factors. For instance, among obese men and women, the prevalence of hypertension has been reported as 81.0% and 58.0%, low HDL cholesterol as 36.0% and 45.0%, and metabolic syndrome as 18.0% and 10.0%, respectively.23 Although the prevalence of overt CVD was relatively low in our predominantly young cohort, the combination of inherited genetic predisposition and obesity-related vascular injury may accelerate endothelial dysfunction and promote the early onset of ED.24 These observations further support the genetic associations identified in our MR analyses, highlighting the interplay between heritable risk and modifiable lifestyle factors in ED pathogenesis.

Severe endothelial impairment not only increases the likelihood of ED onset but may also attenuate therapeutic responsiveness to phosphodiesterase type 5 inhibitors (PDE5i). Prior evidence indicates that genetic polymorphisms, such as those in the endothelial nitric oxide synthase gene, influence PDE5i efficacy; however, heterogeneity in defining treatment responders complicates interpretation across studies.25 Although our study did not directly assess PDE5i outcomes, the demonstrated causal association between familial CVD history and profound vascular impairment suggests that genetically susceptible individuals may represent a subgroup at elevated risk of PDE5i non-response. This hypothesis warrants further exploration. Future pharmacogenetic studies should systematically investigate the interaction between familial CVD-related genetic variants, endothelial dysfunction severity, and treatment response, with the ultimate goal of refining precision medicine strategies for ED management.

In this study, MR analyses demonstrated that maternal history of CVD was associated with a 7.9-fold increased risk of ED compared with men whose mothers were unaffected. Similarly, paternal CVD history conferred a 3.2-fold higher risk of ED relative to those without paternal disease. These findings are consistent with prior evidence indicating that an FH-CVD elevates the genetic predisposition to ED. Furthermore, our study identified a notable disparity in physician awareness: urologists demonstrated greater recognition of the association between CVD and ED than did cardiologists.26 Building on this observation, and supported by both previous literature and our present results, it is essential that cardiologists actively counsel young men with an FH-CVD regarding their heightened susceptibility to ED. Enhanced clinical education and preventive guidance in this population have the potential to significantly improve long-term physical and psychological outcomes.

The present study deliberately focused on a relatively young male cohort (mean age: 33.7 years), offering distinct methodological advantages for delineating the genetic contribution of familial CVD to ED risk. The deliberate inclusion of younger participants enabled evaluation of early-stage ED as a potential marker of subclinical cardiovascular pathology in individuals with inherited susceptibility to CVD. This approach minimized confounding by age-related vascular degeneration and multimorbidity, thereby providing a clearer lens through which to assess the role of genetic predisposition in ED onset. Importantly, this design established ED as an early clinical indicator of vascular dysfunction in genetically vulnerable men, thereby informing opportunities for timely intervention. Although the magnitude of this association may vary across age groups as a result of cumulative exposure to environmental risk factors, such as long-standing metabolic dysfunction or progressive atherosclerosis, the MR findings presented here reflect lifelong genetic susceptibility, which remains biologically plausible irrespective of age. Extending this line of investigation to older populations could determine whether hereditary risk persists when superimposed on acquired comorbidities, thereby informing age-specific prevention and management strategies. Importantly, the identification of a strong association in younger men underscores the clinical value of early risk stratification. Interventions implemented before the onset of irreversible vascular injury may confer greater therapeutic benefit, reinforcing the importance of proactive monitoring and preventive care in this high-risk population.

The primary limitation of this study lies in its modest sample size, particularly the relatively small control cohort (n = 65). This limitation reflects inherent methodological challenges in recruiting young, rigorously phenotyped healthy males for urological research. Nonetheless, a priori power analysis indicated >95% statistical power (α = 0.05) to detect clinically meaningful differences in primary outcomes based on observed effect sizes, mitigating concerns regarding underpowered analyses. Furthermore, the MR component leveraged large-scale genetic datasets, which provided independent validation of the clinical findings and strengthened methodological robustness. Future investigations employing larger and more diverse samples will be critical for improving precision and enhancing the generalizability of these results.

This study applied MR to examine the bidirectional genetic susceptibility linking FH-CVD with ED. The findings demonstrate that genetic predisposition to both paternal and maternal CVD significantly increases the risk of ED. Complementing these genetic insights, our clinical cohort analysis revealed a clear trend of higher ED incidence among Chinese men with an FH-CVD. Together, these results extend beyond conventional observational research, providing novel evidence that integrates clinical and genetic perspectives. Clinically, the data underscore the need for heightened vigilance in men with a parental CVD history. Such individuals should be prioritized for early risk stratification, screening, and preventive interventions aimed at reducing both ED and downstream cardiovascular burden.

AUTHOR CONTRIBUTIONS

DJL conceptualized the study, developed the methodology, conducted analysis and investigation, secured resources, drafted the original manuscript, and reviewed and edited the manuscript. BYX curated data and acquired funding. YL and LL curated data and co-drafted the original manuscript. CTZ contributed to methodology development, oversaw project administration, and reviewed and edited the manuscript. XCL secured resources, developed methodology, conducted analysis and investigation, oversaw project administration, and reviewed and edited the manuscript. All authors read and approved the final manuscript.

COMPETING INTERESTS

All authors declare no competing interests.