The causal association between seven drugs and erectile dysfunction: a Mendelian randomization study

Abstract

Objective:

Many studies have shown that patients develop erectile dysfunction (ED) after taking or aggravating certain drugs. However, other studies have considered such conclusions to be inaccurate. To explore the genetically predicted associations between drug treatment and ED, we used publicly available genome-wide association study (GWAS) data to evaluate the relationship between seven drug treatment regimens and ED using two-sample Mendelian randomization (MR) analysis.

Design:

In this study, a two-sample Mendelian randomized design was used to evaluate the causal relationship between 40 drugs and the risk of ED using publicly available pooled data from the GWAS.

Methods:

We employed five methods for MR analysis: MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, weighted mode, MR-Egger intercept test, MR pleiotropy residual sum, and outlier global test to identify horizontal pleiotropy. Cochran’s Q statistics were used for instrument heterogeneity tests, and the leave-one-out method was used for sensitivity analysis.

Results:

The results showed that simvastatin (p = 0.023), ramipril (p = 0.041), metformin (p = 0.00061), gliclazide (p = 0.015), atorvastatin (p = 0.037), atenolol (p = 0.0052), aspirin (p = 0.051), and simvastatin, and five other drugs were potentially associated with ED. After excluding confounding single-nucleotide polymorphisms (SNPs), the p-value of aspirin was slightly above 0.05, suggesting that aspirin may not have a potential causal relationship with ED, warranting further investigation to confirm this finding. No potential causal relationships were found between the remaining 33 exposures and ED.

Conclusion:

Genetically predicted associations suggest that there may be potential causal relationships between simvastatin, ramipril, metformin, gliclazide, atorvastatin, atenolol, and ED, which require further research.

Plain language summary

Using the association research data of large-scale publicly available population genetic information samples and adopting the randomly assigned association research method, the associations between seven drugs and erectile dysfunction were explored

Why was the study done? The results of studies on the association between certain drugs and erectile dysfunction are controversial, which may hinder us from formulating treatment plans for erectile dysfunction and affect the therapeutic effect of patients with erectile dysfunction.

What did the researchers do? The research team collected genome-wide association study data on 40 drugs and erectile dysfunction, used a randomly assigned association study method to explore the association between them, and the accuracy of the results was verified.

What did the researchers find? Among the 40 drugs, only seven are associated with erectile dysfunction. They are simvastatin, ramipril, metformin, gliclazide, atorvastatin, atenolol, and aspirin showed a trend toward increased risk; however, the p-value of aspirin was slightly above 0.05, warranting further investigation to confirm this finding.

What do the findings mean? This study explored the adverse effects of seven drugs on erectile dysfunction, providing a basis for formulating treatment plans for patients with erectile dysfunction who have other underlying diseases, and avoiding the aggravation of erectile dysfunction in patients.

Keywords

drug erectile dysfunction genome-wide association study (GWAS)incidence risk Mendelian randomization

Introduction

Erectile dysfunction (ED) is a common male sexual dysfunction that is defined as difficulty in obtaining and maintaining sufficient erections for satisfactory sexual performance.¹ ED affects men of all ages, and the prevalence of ED in middle-aged and elderly male patients is 6%–64%, and the risk increases with age.² ED can be caused by various physical and psychological factors. In the central nervous system, sexual arousal and erection were modulated by nitric oxide (NO). Deactivation and reduction of endothelium-derived NO in patients with ED result in increased vasoconstriction and decreased blood flow and oxygen supply, which facilitates the production of oxygen-free radicals, an inflammatory matrix favoring cavernous fibrosis, and ED.³ The most common decrease in testosterone levels may also affect sexual function in older men.⁴ Patients with hyperlipidemia, hypertension, diabetes, or depression also have a significantly increased risk of ED; approximately 42% of patients diagnosed with ED have hyperlipidemia, 40% have hypertension, and 20% have diabetes.⁵ The possibility of ED in diabetic patients is 3.5 times higher than that in non-diabetic patients.⁶ ED patients and cardiovascular disease (CVD) patients have many of the same risk factors, including smoking, obesity, and metabolic syndrome.¹ Many patients will have symptoms of ED. Correspondingly, in a questionnaire survey, most ED patients had a variety of cardiac risk factors.⁷ Adverse reactions to antihypertensive drugs and antidepressants can also cause ED, and erectile function may not be restored after drug withdrawal.⁸ Patients with ED are more likely to have hypertension, diabetes, or CVD. When patients with ED use drugs to treat CVD and other diseases simultaneously, these drugs may also have some effects, which could increase the risk of ED or aggravate ED in patients. Therefore, it is necessary to comprehensively examine the effects of drugs other than ED treatment on ED and provide suggestions for the prevention and treatment of ED.

Several studies have shown that certain drugs, such as antihypertensive drugs and antidepressants, can cause or aggravate ED. In a Propensity Score-Matched Cohort Study, allopurinol, a uric acid-lowering drug, affected erectile function.⁹ The instructions suggest that the incidence of ED caused by arcoxia (90 mg) is between 0.1% and 2%, lisinopril and lisinopril + hydrochlorothiazide 10 mg/12.5 mg tablet may also have adverse reactions of impotence. The results of the current studies on the effects of aspirin on ED are inconsistent. Previous studies suggested that aspirin may be beneficial. Some studies suggest that aspirin does not affect erectile function, whereas several other studies have pointed out that its effect on prostaglandin production is detrimental to ED.¹⁰ A clinical trial found that patients taking beta-blockers such as atenolol were 65.9% more likely to have ED.¹¹ One study reported that the International Index of Erectile Function-5 (IIEF-5) score of patients taking atorvastatin was significantly reduced.¹² Male patients taking bendroflumethiazide also showed a higher incidence of impotence.¹³ Gliclazide and metformin can also increase the risk of ED.^14,15 The selective serotonin reuptake inhibitor citalopram often causes or aggravates ED.¹⁶ Ramipril can reduce oxidative stress and significantly improve the endothelial function of the cavernous tissue in mice¹⁷; however, in a study on predicting cardiovascular events in patients with ED, ramipril did not significantly improve or aggravate the effect of ED.¹⁸ Trivedi et al.¹⁹ found that simvastatin significantly improved the sexual health-related quality of life of subjects, but its effect on erectile function was not significant. According to a US review, testosterone replacement therapy can improve sexual function in patients with hypogonadism, and a testogel combined with sildenafil can improve erectile response in patients treated with sildenafil alone.²⁰ A European Mendelian randomization (MR) study showed no significant association between thyroid function and sexual function in terms of genetic prediction.²¹ However, levothyroxine is beneficial for improving sexual function in patients with hypothyroidism.²² In a clinical trial of 21 patients with hypothyroidism treated with levothyroxine, 11 were treated with levothyroxine and liothyronine. The effect of the combined group on sexual function was slightly better than that of levothyroxine alone, and its effect on improving sexual desire was beneficial for patients with impaired desire.²³ The effects of certain drugs on erectile function are rather complex, and current research presents inconsistent findings. This may be due to the fact that existing studies have failed to exclude the effects of confounding factors and reverse causality, resulting in biased conclusions and associations. This study aimed to apply MR to eliminate the influence of confounding factors and reverse causality, and to derive more reliable and referenceable conclusions.

In recent years, the application of MR analysis to assess the relationships between exposure and outcomes has grown significantly.²⁴ MR analysis differs from traditional observational studies in that it employs single-nucleotide polymorphisms (SNPs) related to exposure as instrumental variables (IVs), thereby establishing a connection between risk factors and disease.²⁵ Given that genetic variations are randomly allocated during meiosis, MR studies resemble genetic randomized controlled trials,²⁶ effectively ruling out possible reverse causality and other confounding factors. In this study, we performed a two-sample MR analysis to investigate the association between 40 drugs and ED.

Materials and methods

Study design

We used a two-sample MR analysis to evaluate the effects of the 40 drugs on ED. The selected IVs met three important assumptions (Figure 1): (1) IVs were strongly correlated with drugs, (2) IVs were not related to confounding factors, and (3) there was no direct correlation between IVs and ED, except through a link with drugs.

Figure 1.

The three assumptions of the MR analysis.

The reporting of this study conformed to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. (Detailed information is provided in Supplemental Material: STROBE-MR-checklist.)

Data source

Our exposure data was extracted from the IEU Open genome-wide association study (GWAS) Project, a database of 346,782,922,639 genetic associations from 50,044 GWAS summaries. The population included in our study are all Europeans, and the exposure in this study included 40 drugs (the subjects selection flowchart is presented in Supplemental Figure 1): allopurinol (N = 462,933), amlodipine (N = 462,933), arcoxia (N = 337,159), aspirin (N = 462,933), atenolol (N = 462,933), atorvastatin (N = 462,933), bendroflumethiazide (N = 462,933), carbimazole (N = 337,159), cipralex (N = 337,159), co-amilofruse (N = 337,159), dothiepin (N = 337,159), ezetimibe (N = 462,933), gliclazide (N = 462,933), hydroxocobalamin (N = 337,159), indivina (N = 337,159), insulin (N = 462,933), isosorbide dinitrate (N = 337,159), kapake (N = 337,159), letrozole (N = 337,159), levothyroxine sodium (N = 462,933), liothyronine (N = 337,159), lipitor (N = 462,933), lisinopril (N = 462,933), lisinopril + hydrochlorothiazide (N = 337,159), logynon (N = 337,159), metformin (N = 462,933), methotrexate (N = 462,933), morphine (N = 337,159), paracetamol (N = 462,933), ramipril (N = 462,933), rhinocort (N = 337,159), rosuvastatin (N = 462,933), salbutamol (N = 462,933), seretide 50 evohaler (N = 462,933), simvastatin (N = 462,933), testogel (N = 337,159), thyroxine (N = 462,933), ventolin (N = 462,933), warfarin (N = 462,933), xalatan (N = 462,933). Outcomes for ED (N = 223,805, including Ncase = 6175 and Ncontrol = 217,630). Detailed information is provided in Table 1.

Table 1.

Detailed information about the aggregated GWAS results.

GWAS ID	Trait	Author	Consortium	ncase	ncontrol	Sample size	SNPs (n)	Population
ukb-b-15895	Allopurinol	Ben Elsworth	MRC-IEU	5243	457,690	462,933	9,851,867	European
ukb-b-9207	Amlodipine	Ben Elsworth	MRC-IEU	18,713	444,220	462,933	9,851,867	European
ukb-a-185	Arcoxia	Neale	Neale Lab	98	337,061	337,159	10,894,596	European
ukb-b-8755	Aspirin	Ben Elsworth	MRC-IEU	61,702	401,231	462,933	9,851,867	European
ukb-b-11632	Atenolol	Ben Elsworth	MRC-IEU	17,884	445,049	462,933	9,851,867	European
ukb-b-10008	Atorvastatin	Ben Elsworth	MRC-IEU	13,851	449,082	462,933	9,851,867	European
ukb-b-18799	Bendroflumethiazide	Ben Elsworth	MRC-IEU	25,767	437,166	462,933	9,851,867	European
ukb-a-140	Carbimazole	Neale	Neale Lab	275	336,884	337,159	10,894,596	European
ukb-a-189	Cipralex	Neale	Neale Lab	297	336,862	337,159	10,894,596	European
ukb-a-173	Co-amilofruse	Neale	Neale Lab	326	336,833	337,159	10,894,596	European
ukb-a-147	Dothiepin	Neale	Neale Lab	138	337,021	337,159	10,894,596	European
ukb-b-6474	Ezetimibe	Ben Elsworth	MRC-IEU	2701	460,232	462,933	9,851,867	European
ukb-b-8602	Gliclazide	Ben Elsworth	MRC-IEU	3840	459,093	462,933	9,851,867	European
ukb-a-134	Hydroxocobalamin	Neale	Neale Lab	84	337,075	337,159	10,894,596	European
ukb-a-181	Indivina	Neale	Neale Lab	104	337,055	337,159	10,894,596	European
ukb-b-15445	Insulin	Ben Elsworth	MRC-IEU	4537	458,396	462,933	9,851,867	European
ukb-a-119	Isosorbide dinitrate	Neale	Neale Lab	81	337,078	337,159	10,894,596	European
ukb-a-125	Kapake	Neale	Neale Lab	94	337,065	337,159	10,894,596	European
ukb-a-174	Letrozole	Neale	Neale Lab	208	336,951	337,159	10,894,596	European
ukb-b-17918	Levothyroxine sodium	Ben Elsworth	MRC-IEU	18,947	443,986	462,933	9,851,867	European
ukb-a-157	Liothyronine	Neale	Neale Lab	86	337,073	337,159	10,894,596	European
ukb-b-18062	Lipitor	Ben Elsworth	MRC-IEU	3349	459,584	462,933	9,851,867	European
ukb-b-12095	Lisinopril	Ben Elsworth	MRC-IEU	12,787	450,146	462,933	9,851,867	European
ukb-a-127	Lisinopril + hydrochlorothiazide	Neale	Neale Lab	114	337,045	337,159	10,894,596	European
ukb-a-133	Logynon	Neale	Neale Lab	141	337,018	337,159	10,894,596	European
ukb-b-14609	Metformin	Ben Elsworth	MRC-IEU	11,552	451,381	462,933	9,851,867	European
ukb-b-12209	Methotrexate	Ben Elsworth	MRC-IEU	2454	460,479	462,933	9,851,867	European
ukb-a-137	Morphine	Neale	Neale Lab	194	336,965	337,159	10,894,596	European
ukb-b-8147	Paracetamol	Ben Elsworth	MRC-IEU	85,782	377,151	462,933	9,851,867	European
ukb-b-11895	Ramipril	Ben Elsworth	MRC-IEU	21,448	441,485	462,933	9,851,867	European
ukb-a-144	Rhinocort	Neale	Neale Lab	145	337,014	337,159	10,894,596	European
ukb-b-13664	Rosuvastatin	Ben Elsworth	MRC-IEU	2870	460,063	462,933	9,851,867	European
ukb-b-12301	Salbutamol	Ben Elsworth	MRC-IEU	5499	457,434	462,933	9,851,867	European
ukb-b-17836	Seretide 50 evohaler	Ben Elsworth	MRC-IEU	5409	457,524	462,933	9,851,867	European
ukb-b-11268	Simvastatin	Ben Elsworth	MRC-IEU	52,427	410,506	462,933	9,851,867	European
ukb-a-192	Testogel	Neale	Neale Lab	119	337,040	337,159	10,894,596	European
ukb-b-9971	Thyroxine	Ben Elsworth	MRC-IEU	5469	457,464	462,933	9,851,867	European
ukb-b-13148	Ventolin	Ben Elsworth	MRC-IEU	13,244	449,689	462,933	9,851,867	European
ukb-b-13248	Warfarin	Ben Elsworth	MRC-IEU	4623	458,310	462,933	9,851,867	European
ukb-b-17616	Xalatan	Ben Elsworth	MRC-IEU	1274	461,659	462,933	9,851,867	European
ebi-a-GCST006956	Erectile dysfunction	Bovijn J	/	6175	217,630	223,805	9,310,196	European

GWAS, genome-wide association study; SNP, single-nucleotide polymorphisms.

Selection of genetic instruments

To identify the IVs that met the three key MR criteria, we implemented several quality control measures. Initially, we chose SNPs with a strong correlation to exposure (p < 5 × 10⁻⁸) as IVs. We then established criteria (r² < 0.001 and window size of 10,000) to filter out SNPs exhibiting high linkage disequilibrium and excluded those with palindromic structures. We conducted bidirectional harmonization to align the effect alleles across the exposure and outcome datasets and removed SNPs with incompatible alleles. Ambiguous palindromic SNPs were excluded unless allele frequency information allowed for an unambiguous alignment. In addition, we utilized the F-statistic to assess the strength of the selected IVs²⁷ and established a threshold of F > 10 to avoid potential bias from weak instruments.²⁸ We calculated the F-statistics for each SNP (F = β²/SE²) and ensured that all the instruments exceeded the conventional threshold of F > 10, indicating sufficient strength. We also reported the mean F-statistic and proportion of variance explained (r²) by the instrument set; the F-statistics and r² values are provided in detail in Supplemental Tables 1–7. Additionally, confounding SNPs were excluded by searching for SNP information in the GWAS catalog and PubMed.

Statistical analysis

The primary method for evaluating the relationship between drugs and ED is the inverse variance-weighted (IVW) approach. We supplemented this with other techniques such as MR-Egger regression, weighted median, simple mode, and weighted mode. Cochran’s Q statistics were employed to detect instrument heterogeneity, with a p-value of less than 0.05 indicating heterogeneity.²⁹ Horizontal pleiotropy was assessed using the MR-Egger intercept test and the MR-PRESSO global test, where a p-value less than 0.05 suggested pleiotropy.^30,31 In addition, we utilized the MR-PRESSO method to detect any potential outliers and, upon identification, excluded them and repeated the MR analysis. Finally, we conducted a sensitivity analysis using a leave-one-out approach. All analyses were conducted using the “TwoSampleMR” and “MR-PRESSO” packages in R version 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria).

Results

Results of SNPs selection and the weak IV test

We used MR analysis for ED with 40 different drugs. For simvastatin exposure, rs11591147, rs1260326, rs12916, rs1367117, rs1421085, rs2980888, rs34042070, rs7412, and rs964184 were excluded as confounding factors. In addition, rs10195252, rs1421085, rs1800961, rs459193, rs62106258, rs780093, and rs987237 were also excluded because of confounding factors of metformin exposure; rs2943650 and rs56094641 were confounding factors for gliclazide. Confounding factors of atorvastatin included rs12916, rs13022873, rs28601761, and rs964184. And rs10774625, rs7412 were excluded as confounding factors for aspirin. In the MR Analysis for gliclazide, rs59442809 was removed as palindromic with intermediate allele frequencies. Similarly, rs10738606 in atorvastatin exposure was removed because it was palindromic with intermediate allele frequencies. In addition, rs10738606 in atenolol exposure and rs7310615 in aspirin exposure were removed as palindromic with intermediate allele frequencies. Detailed information on the IVs for Simvastatin, Ramipril, Metformin, Gliclazide, Atorvastatin, Atenolol, and Aspirin is provided in Supplemental Tables 1–7. The F-statistics for all IVs exceeded 10, indicating that the MR analysis results were probably not influenced by weak IV bias.

Results of MR analysis

The preliminary results of the IVW analysis are listed in Table 2. Simvastatin (p = 0.013), ramipril (p = 0.041), metformin (p = 0.00099), gliclazide (p = 0.0096), atorvastatin (p = 0.022), atenolol (p = 0.0073), aspirin (p = 0.019); these seven drugs have potential causal relationships with ED. Other drugs had no relationship with the occurrence of ED (p > 0.05). We subsequently performed an MR analysis after excluding confounding SNPs for these seven drugs. The results following this adjustment are presented in Table 3, which shows that the p-values for simvastatin, ramipril, metformin, gliclazide, atorvastatin, and atenolol remained below 0.05, while the p-value for aspirin was slightly above 0.05 (IVW beta = 2.65, p = 0.051). However, this observation required further validation. The results of the MR-Egger regression, weighted median, simple mode, and weighted mode analyses of seven drugs, such as simvastatin, were consistent with the results of the IVW analysis. Such as simvastatin, IVW (beta = 1.67, odds ratio, OR (95% confidence interval, CI) = 5.32 (1.26–22.43), p = 0.023), MR-Egger regression (beta = 0.072, OR (95% CI) = 1.08 (0.037–31.58), p = 0.97), weighted median (beta = 1.27, OR (95% CI) = 3.56 (0.45–28.30), p = 0.23), simple mode (beta = 1.04, OR (95% CI) = 2.84 (0.092–87.52), p = 0.56), weighted mode (beta = 0.97, OR (95% CI) = 2.65 (0.17–40.63), p = 0.49). For ramipril, IVW (beta = 4.41, OR (95% CI) = 82.56 (1.21–5642.48), p = 0.041), MR-Egger regression (beta = 18.22, OR (95% CI) = 8.18 × 10⁷ (0.57–1.17 × 10¹⁶), p = 0.090), weighted median (beta = 3.79, OR (95% CI) = 44.07 (0.20–9831.47), p = 0.17), simple mode (beta = 2.67, OR (95% CI) = 14.40 (0.0030–66080.30), p = 0.55), weighted mode (beta = 2.48, OR (95% CI) = 11.94 (0.0020–58399.33), p = 0.58). The results of the IVW, MR-Egger, weighted median, simple mode, and weighted mode analyses are consistent.

Table 2.

The results of IVW about the aggregated GWAS results.

id.exposure	id.outcome	Outcome	Exposure	Method	nsnp	b	se	pval
ukb-b-14609	ebi-a-GCST006956	Erectile dysfunction	Metformin	IVW	46	4.61	1.40	0.00098
ukb-b-11632	ebi-a-GCST006956	Erectile dysfunction	Atenolol	IVW	11	5.99	2.23	0.0072
ukb-b-8602	ebi-a-GCST006956	Erectile dysfunction	Gliclazide	IVW	9	13.80	5.33	0.0096
ukb-b-11268	ebi-a-GCST006956	Erectile dysfunction	Simvastatin	IVW	41	1.38	0.55	0.013
ukb-b-8755	ebi-a-GCST006956	Erectile dysfunction	Aspirin	IVW	13	2.95	1.26	0.019
ukb-b-10008	ebi-a-GCST006956	Erectile dysfunction	Atorvastatin	IVW	21	3.17	1.39	0.022
ukb-b-11895	ebi-a-GCST006956	Erectile dysfunction	Ramipril	IVW	11	4.41	2.16	0.041
ukb-b-13248	ebi-a-GCST006956	Erectile dysfunction	Warfarin	IVW	9	6.82	3.89	0.080
ukb-a-157	ebi-a-GCST006956	Erectile dysfunction	Liothyronine	IVW	18	40.73	23.84	0.088
ukb-a-127	ebi-a-GCST006956	Erectile dysfunction	Lisinopril + hydrochlorothiazide	IVW	9	−47.64	29.85	0.11
ukb-a-125	ebi-a-GCST006956	Erectile dysfunction	Kapake	IVW	17	−28.75	18.40	0.12
ukb-a-140	ebi-a-GCST006956	Erectile dysfunction	Carbimazole	IVW	7	26.67	17.18	0.12
ukb-a-137	ebi-a-GCST006956	Erectile dysfunction	Morphine	IVW	5	48.66	32.18	0.13
ukb-a-133	ebi-a-GCST006956	Erectile dysfunction	Logynon	IVW	5	43.12	30.91	0.16
ukb-a-181	ebi-a-GCST006956	Erectile dysfunction	Indivina	IVW	14	31.57	23.66	0.18
ukb-b-8147	ebi-a-GCST006956	Erectile dysfunction	Paracetamol	IVW	14	−1.30	0.99	0.19
ukb-b-15445	ebi-a-GCST006956	Erectile dysfunction	Insulin	IVW	9	2.43	2.26	0.28
ukb-b-12301	ebi-a-GCST006956	Erectile dysfunction	Salbutamol	IVW	5	8.11	7.54	0.28
ukb-b-9207	ebi-a-GCST006956	Erectile dysfunction	Amlodipine	IVW	24	1.29	1.38	0.35
ukb-b-15895	ebi-a-GCST006956	Erectile dysfunction	Allopurinol	IVW	15	2.16	2.50	0.39
ukb-b-13664	ebi-a-GCST006956	Erectile dysfunction	Rosuvastatin	IVW	6	5.37	6.78	0.43
ukb-b-18799	ebi-a-GCST006956	Erectile dysfunction	Bendroflumethiazide	IVW	40	0.67	0.94	0.48
ukb-a-185	ebi-a-GCST006956	Erectile dysfunction	Arcoxia	IVW	15	−14.49	21.59	0.50
ukb-a-147	ebi-a-GCST006956	Erectile dysfunction	Dothiepin	IVW	10	−14.69	22.52	0.51
ukb-b-12095	ebi-a-GCST006956	Erectile dysfunction	Lisinopril	IVW	9	1.93	3.07	0.53
ukb-a-192	ebi-a-GCST006956	Erectile dysfunction	Testogel	IVW	21	8.75	14.37	0.54
ukb-b-9971	ebi-a-GCST006956	Erectile dysfunction	Thyroxine	IVW	17	−1.51	2.51	0.55
ukb-b-18062	ebi-a-GCST006956	Erectile dysfunction	Lipitor	IVW	5	3.62	7.08	0.61
ukb-b-6474	ebi-a-GCST006956	Erectile dysfunction	Ezetimibe	IVW	6	3.24	6.35	0.61
ukb-a-134	ebi-a-GCST006956	Erectile dysfunction	Hydroxocobalamin	IVW	11	−12.41	26.26	0.64
ukb-b-17836	ebi-a-GCST006956	Erectile dysfunction	Seretide 50 evohaler	IVW	8	3.31	7.51	0.66
ukb-b-17616	ebi-a-GCST006956	Erectile dysfunction	Xalatan	IVW	5	−9.05	23.42	0.70
ukb-a-119	ebi-a-GCST006956	Erectile dysfunction	Isosorbide dinitrate	IVW	18	−5.97	16.36	0.72
ukb-a-174	ebi-a-GCST006956	Erectile dysfunction	Letrozole	IVW	7	−13.10	36.39	0.72
ukb-a-189	ebi-a-GCST006956	Erectile dysfunction	Cipralex	IVW	3	−13.22	48.67	0.79
ukb-a-173	ebi-a-GCST006956	Erectile dysfunction	Co-amilofruse	IVW	5	−6.11	25.35	0.81
ukb-a-144	ebi-a-GCST006956	Erectile dysfunction	Rhinocort	IVW	9	−4.18	18.16	0.82
ukb-b-13148	ebi-a-GCST006956	Erectile dysfunction	Ventolin	IVW	24	−0.38	1.69	0.82
ukb-b-17918	ebi-a-GCST006956	Erectile dysfunction	Levothyroxine sodium	IVW	77	−0.084	0.59	0.89
ukb-b-12209	ebi-a-GCST006956	Erectile dysfunction	Methotrexate	IVW	4	−0.42	5.39	0.94

GWAS, genome-wide association study; IVW, inverse variance-weighted.

Table 3.

Results of the two-sample MR analyses.

id.exposure	id.outcome	Exposure	Outcome	Method	SNPs (n)	Beta	se	pval	OR(95% CI)
ukb-b-11268	ebi-a-GCST006956	Simvastatin	Erectile dysfunction	MR-Egger	32	0.072	1.72	0.97	1.08(0.037–31.58)
				Weighted median	32	1.27	1.06	0.23	3.56(0.45–28.30)
				IVW	32	1.67	0.73	0.023	5.32(1.26–22.43)
				Simple mode	32	1.04	1.75	0.56	2.84(0.092–87.52)
				Weighted mode	32	0.97	1.39	0.49	2.65(0.17–40.63)
ukb-b-11895	ebi-a-GCST006956	Ramipril	Erectile dysfunction	MR-Egger	11	18.22	9.58	0.090	8.18E + 7(0.57–1.17E + 16)
				Weighted median	11	3.79	2.76	0.17	44.07(0.20–9831.47)
				IVW	11	4.41	2.16	0.041	82.56(1.21–5642.48)
				Simple mode	11	2.67	4.30	0.55	14.40(0.0030–66,080.30)
				Weighted mode	11	2.48	4.33	0.58	11.94(0.0020–58,399.33)
ukb-b-14609	ebi-a-GCST006956	Metformin	Erectile dysfunction	MR-Egger	39	7.29	3.84	0.066	1458.62(0.78–2.72E + 6)
				Weighted median	39	4.99	2.21	0.024	146.75(1.93–11,169.64)
				IVW	39	5.21	1.52	0.00061	183.07(9.29–3606.16)
				Simple mode	39	5.51	4.24	0.20	247.11(0.061–9.99E + 5)
				Weighted mode	39	5.34	2.18	0.019	208.00(2.88–15,007.47)
ukb-b-8602	ebi-a-GCST006956	Gliclazide	Erectile dysfunction	MR-Egger	7	7.69	12.07	0.55	2183.84(0–4.12E + 13)
				Weighted median	7	11.50	5.58	0.039	98775.60(1.77–5.51E + 9)
				IVW	7	13.30	5.48	0.015	6.00E + 5(12.91–2.79E + 10)
				Simple mode	7	9.06	9.32	0.37	8604.90(0–7.36E + 11)
				Weighted mode	7	11.53	5.99	0.10	1.02E + 5(0.81–1.28E + 10)
ukb-b-10008	ebi-a-GCST006956	Atorvastatin	Erectile dysfunction	MR-Egger	18	1.82	3.48	0.61	6.17(0.0070–5617.49)
				Weighted median	18	3.00	2.13	0.16	20.10(0.31–1298.59)
				IVW	18	3.18	1.52	0.037	23.94(1.21–472.20)
				Simple mode	18	2.61	3.36	0.45	13.57(0.019–9819.53)
				Weighted mode	18	1.83	2.97	0.55	6.23(0.018–2102.57)
ukb-b-11632	ebi-a-GCST006956	Atenolol	Erectile dysfunction	MR-Egger	10	4.78	10.55	0.66	118.62(0–1.14E + 11)
				Weighted median	10	6.47	3.24	0.046	646.59(1.12–3.74E + 5)
				IVW	10	6.85	2.45	0.0052	944.16(7.73–1.15E + 5)
				Simple mode	10	6.65	5.32	0.24	772.01(0.023–2.62E + 7)
				Weighted mode	10	5.65	5.06	0.29	285.17(0.014–5.78E + 6)
ukb-b-8755	ebi-a-GCST006956	Aspirin	Erectile dysfunction	MR-Egger	12	5.06	3.53	0.18	157.45(0.16–1.58E + 5)
				Weighted median	12	3.11	1.66	0.061	22.39(0.87–579.38)
				IVW	12	2.65	1.36	0.051	14.17(0.99–203.97)
				Simple mode	12	3.23	2.88	0.29	25.33(0.089–7181.85)
				Weighted mode	12	3.10	2.12	0.17	22.15(0.35–1420.28)

CI, confidence interval; IVW, inverse variance weighted; MR, Mendelian randomization; OR, odds ratio; SNP, single-nucleotide polymorphism.

The results of sensitivity analysis

Table 4 displays the findings from Cochran’s Q heterogeneity test, MR-Egger intercept test, and MR-PRESSO global test. The p-values from Cochran’s Q test for aspirin, atenolol, atorvastatin, gliclazide, ramipril, and simvastatin were all >0.05, suggesting an absence of heterogeneity. Cochran’s Q test p-value for metformin was less than 0.05, indicating a pleiotropic effect, and random effect IVW MR analysis should be used.³² No outliers were detected using the MR-PRESSO global test, and the correction value was NA. The leave-one-out analysis demonstrated that the findings remained consistent following the removal of each SNP. Scatter plots were used to represent the predicted effects of the IVs on exposure and outcome. The sensitivity analysis confirmed the reliability of the MR analysis results (Figures 2 –8). Given the number of exposures/outcomes tested, we applied the Benjamini–Hochberg FDR correction to adjust for multiple comparisons. The correction results are presented in Supplemental Table 8. The results remained unchanged following FDR corrections and were consistent with the previous conclusions.

Table 4.

Reliability test of MR analysis results.

id.exposure	id.outcome	Exposure	Outcome	Method	Q	Q_df	Q_pval	MR-Egger intercept test p	MR-PRESSO global test p
ukb-b-11268	ebi-a-GCST006956	Simvastatin	Erectile dysfunction	MR-Egger	32.30	30	0.35
				IVW	33.43	31	0.35	0.31	0.36
ukb-b-11895	ebi-a-GCST006956	Ramipril	Erectile dysfunction	MR-Egger	2.80	9	0.97
				IVW	4.99	10	0.89	0.17	0.89
ukb-b-14609	ebi-a-GCST006956	Metformin	Erectile dysfunction	MR-Egger	55.93	37	0.024
				IVW	56.45	38	0.027	0.56	NA (Not Available)
ukb-b-8602	ebi-a-GCST006956	Gliclazide	Erectile dysfunction	MR-Egger	7.94	5	0.16
				IVW	8.39	6	0.21	0.62	0.31
ukb-b-10008	ebi-a-GCST006956	Atorvastatin	Erectile dysfunction	MR-Egger	7.10	16	0.97
				IVW	7.29	17	0.98	0.67	0.98
ukb-b-11632	ebi-a-GCST006956	Atenolol	Erectile dysfunction	MR-Egger	5.30	8	0.73
				IVW	5.34	9	0.80	0.84	0.87
ukb-b-8755	ebi-a-GCST006956	Aspirin	Erectile dysfunction	MR-Egger	13.80	10	0.18
				IVW	14.57	11	0.20	0.47	0.30

IVW, inverse variance weighted; MR, Mendelian randomization.

Figure 2.

Effect of simvastatin on ED. (a) Scatter plot of the causal association of simvastatin on ED. (b) Funnel plot of the causal association of simvastatin on ED. (c) Forest plot of the leave-one-out analysis. (d) Forest plot of the causal association of simvastatin on ED.

Figure 3.

Effect of ramipril on ED. (a) Scatter plot of the causal association of ramipril on ED. (b) Funnel plot of the causal association of ramipril on ED. (c) Forest plot of the leave-one-out analysis. (d) Forest plot of the causal association of ramipril on ED.

Figure 4.

Effect of metformin on ED. (a) Scatter plot of the causal association of metformin on ED. (b) Funnel plot of the causal association of metformin on ED. (c) Forest plot of the leave-one-out analysis. (d) Forest plot of the causal association of metformin on ED.

Figure 5.

Effect of gliclazide on ED. (a) Scatter plot of the causal association of gliclazide on ED. (b) Funnel plot of the causal association of gliclazide on ED. (c) Forest plot of the leave-one-out analysis. (d) Forest plot of the causal association of gliclazide on ED.

Figure 6.

Effect of atorvastatin on ED. (a) Scatter plot of the causal association of atorvastatin on ED. (b) Funnel plot of the causal association of atorvastatin on ED. (c) Forest plot of the leave-one-out analysis. (d) Forest plot of the causal association of atorvastatin on ED.

Figure 7.

Effect of atenolol on ED. (a) Scatter plot of the causal association of atenolol on ED. (b) Funnel plot of the causal association of atenolol on ED. (c) Forest plot of the leave-one-out analysis. (d) Forest plot of the causal association of atenolol on ED.

Figure 8.

Effect of aspirin on ED. (a) Scatter plot of the causal association of aspirin on ED. (b) Funnel plot of the causal association of aspirin on ED. (c) Forest plot of the leave-one-out analysis. (d) Forest plot of the causal association of aspirin on ED.

Discussion

Many studies have been conducted on the effects of certain drugs on ED, but the conclusions of many studies are inconsistent. To the best of our knowledge, this is the first study to use MR analysis to explore the effects of multiple drugs in the ED. Genetically predicted associations suggest potential causal relationships between simvastatin, ramipril, metformin, gliclazide, atorvastatin, atenolol, and ED. After excluding confounding SNPs, the p-value of aspirin was slightly above 0.05, suggesting that aspirin may not have a potential causal relationship with ED. Further investigations are required to confirm this finding. No relationships were found between the remaining 33 exposures and ED.

One meta-analysis showed that simvastatin and atorvastatin significantly increased the IIEF-5 score of patients.³³ Simvastatin can activate the AMPK-SKP2-CARM1 pathway and target PDCD4 expression by enhancing miR-9-5p, thereby enhancing autophagy, reducing penile cavernous fibrosis, and alleviating diabetic ED.^34,35 This differs from our MR results and may require further verification. Atorvastatin significantly increases NO levels, which is considered the cornerstone for improving endothelial dysfunction.³⁶ However, another study using the French Pharmacovigilance System Database included 110,685 spontaneous reports. Fifty-one of the 4471 reports involving statin exposure, these patients developed ED within 75 days, and more than half of the patients recovered after statin discontinuation.³⁷ Impaired lipid metabolism can promote infertility. Statins can regulate lipid metabolism to improve fertility and reduce cholesterol, a precursor of testosterone.³⁸ The decrease in cholesterol may lead to a decrease in testosterone levels, which has an adverse effect on the erectile function of patients. Another MR analysis of atorvastatin showed that it may have an effect on ED.³⁹ Ramipril can improve the endothelial function of cavernous tissue in mice.¹⁷ A survey of patients at high risk of CVD also indicated that ramipril tended to improve erectile function in these patients.⁴⁰ However, a study predicting cardiovascular events in patients found that ramipril does not significantly improve or aggravate ED.¹⁸ In obese mice treated with metformin, intracavernosal pressure and impaired in vitro endothelium-dependent and nitrergic relaxation were restored to normal levels. Researchers believe that metformin may be a treatment option for insulin resistance-related ED.⁴¹ However, patients with type 2 diabetes who use metformin have a higher risk of developing ED and infertility.¹⁵ Few studies have investigated the association between gliclazide and ED. Another MR analysis exploring the relationship between hypoglycemic drugs and ED suggested that gliclazide may have an impact on ED.¹⁴ This result may have also been influenced by confounding factors. A crossover study in 1993 suggested that atenolol had no significant effect on erectile function in patients with hypertension,⁴² but only in 17 subjects. Another study of 44 patients using β-blockers such as atenolol showed that 65.9% of patients had ED.¹¹ Interestingly, Antonello divided 96 patients with CVD into three groups. Patients in group A were treated with atenolol but were not aware of the drug. Patients in group B were informed of the name of the drug but were not told about the side effects of the drug in the ED, and patients in group C were fully aware of the name of the drug and its side effects. Following a 90-day treatment period, the incidence of ED was minimal in group A, with only a single individual affected, whereas groups B and C reported higher rates, with 5 and 10 individuals experiencing ED, respectively. In a follow-up study, except for one patient, placebo and sildenafil had the same effect on the reversal of ED.⁴³ This suggests that the incidence of ED in patients may increase with improvement in cognition of drugs, and patients may be anxious about sexual side effects. There are different opinions on the effects of aspirin in the ED. Bayraktar and Saroukhani conducted a randomized double-blind placebo-controlled experiment on vascular ED and lithium salt-related sexual dysfunction. They concluded that aspirin could improve sexual dysfunction in these patients.^44,45 Another study published by Bayraktar and Albayrak⁴⁶ in 2019, pointed out that the combination of aspirin can improve the safety and efficacy of tadalafil in the treatment of patients with vascular ED, and even the use of aspirin alone can improve erectile function in patients. A large prospective study showed that non-aspirin non-steroidal anti-inflammatory drugs (NSAID) were associated with a 16% increase in the risk of mild to moderate ED, and aspirin was associated with a 16% increase in the risk of severe ED, which seems to indicate that aspirin is a risk factor for ED. However, after controlling for the medical indications of NSAID (the probability of ED in male patients with rheumatoid arthritis was 67%, and indications such as headache and atherosclerotic disease were also associated with an increased risk of ED), the risk association between NSAIDs such as aspirin and ED was not statistically significant.⁴⁷ The results of animal model experiments also showed that aspirin had no effect on erectile function. Although aspirin reduces the production of prostaglandins, the inhibitory effect of aspirin on TXA2 may have no effect on erectile function.⁴⁸ Our initial IVW analysis indicated that these seven drugs have potential causal relationships with ED. We subsequently performed MR analysis after excluding confounding SNPs for these seven drugs, and the p-value for aspirin was slightly above 0.05. This suggests that aspirin did not have a statistically significant effect on ED. The existing research results and the conclusions drawn by this study through the exploration of causal relationships suggest that the impact of drugs on ED may not only be reflected in terms of pharmacodynamics but may also be related to the patient’s other diseases and psychological factors.

Our study has several advantages. Mendelian randomization was used to reduce possible biases, such as confounding factors and reverse causality. We used a large sample size of data from GWAS to reduce the bias of weak IVs. Multiple sensitivity analyses confirmed the validity of the results.

At the same time, our study also has some limitations. The samples included in this study were from European populations, and it remains uncertain whether our findings are applicable to non-European populations. In addition, it is difficult to assess the nonlinear association between these drugs and the occurrence of ED, and the p-value of ramipril is close to 0.05 in the analysis results of IVW, which requires additional GWAS data to further verify. Furthermore, overly high odds ratios for drugs such as atenolol and metformin have also been observed. Their odds ratios were astonishingly high, which may reflect methodological limitations such as weak instrument bias, low event counts, or the impact of rare variant influences.

Conclusion

These results provided genetically predicted associations for the potential effects of simvastatin, ramipril, metformin, gliclazide, atorvastatin, and atenolol on ED. The p-value for aspirin was slightly above 0.05. This suggests that aspirin did not have a statistically significant effect on ED. Furthermore, no potential causal relationships were identified between the remaining 33 exposures and ED. These findings need to be interpreted in the context of confounding factors and require final validation in randomized controlled trials.

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Footnotes

Acknowledgements

In this study, data from publicly accessible GWAS were used. The authors express their gratitude to everyone who participated in the data-collection process.

Declarations

ORCID iDs

Jian Zhan

Jing Liu

Yilan Huang

Longyang Jiang

Supplemental material

Supplemental material for this article is available online.

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