Association between metabolic parameters and erection in erectile dysfunction patients with hyperuricemia

Abstract

The relationship between hyperuricemia (HUA) and erectile dysfunction (ED) remains inadequately understood. Given that HUA is often associated with various metabolic disorders, this study aims to explore the multivariate linear impacts of metabolic parameters on erectile function in ED patients with HUA. A cross-sectional analysis was conducted involving 514 ED patients with HUA in the Department of Andrology, Jiangsu Province Hospital of Chinese Medicine (Nanjing, China), aged 18 to 60 years. General demographic information, medical history, and laboratory results were collected to assess metabolic disturbances. Sexual function was evaluated using the 5-item version of the International Index of Erectile Function (IIEF-5) questionnaire. Based on univariate analysis, variables associated with IIEF-5 scores were identified, and the correlations between them were evaluated. The effects of these variables on IIEF-5 scores were further explored by multiple linear regression models. Fasting plasma glucose (β = −0.628, P < 0.001), uric acid (β = −0.552, P < 0.001), triglycerides (β = −0.088, P = 0.047), low-density lipoprotein cholesterol (β = −0.164, P = 0.027), glycated hemoglobin (HbA1c; β = −0.562, P = 0.012), and smoking history (β = −0.074, P = 0.037) exhibited significant negative impacts on erectile function. The coefficient of determination (R²) for the model was 0.239, and the adjusted R² was 0.230, indicating overall statistical significance (F-statistic = 26.52, P < 0.001). Metabolic parameters play a crucial role in the development of ED. Maintaining normal metabolic indices may aid in the prevention and improvement of erectile function in ED patients with HUA.

INTRODUCTION

In recent decades, the prevalence of hyperuricemia (HUA) has steadily increased, positioning it as one of the major metabolic diseases affecting men’s health worldwide.1 It is estimated that the overall prevalence of HUA in China is 10.4%, with the prevalence in men (10.7%) surpassing that in women (9.9%).2 Hyperuricemia, a well-established risk factor for gout, has been increasingly associated with erectile dysfunction (ED), representing a frequently overlooked risk factor in ED prevention and management. A study involving 85 406 hyperuricemic patients found that the prevalence of ED was approximately 33% (95% confidence interval [CI]: 13%–52%; I²: 99.9%), underscoring the significant burden of ED within this population and suggesting a potential link between elevated uric acid levels and impaired sexual function.3 Furthermore, for every 1 mg dl⁻¹ increase in serum uric acid, the risk of developing ED doubles (odds ratio [OR]: 2.07; 95% CI: 1.63–2.64), emphasizing the critical role of elevated uric acid as a significant risk factor for ED and indicating that even modest increases in uric acid levels can substantially elevate the likelihood of experiencing ED.4 Other studies have demonstrated that hyperuricemic patients have a 1.59-fold higher risk of developing ED compared to those with normal uric acid levels (OR: 1.59; 95% CI: 1.29–1.97), while hyperuricemic patients undergoing uric acid-lowering therapy experience a 27% reduction in the risk of ED.5

Many studies suggest a connection between HUA and ED; however, whether HUA constitutes an independent risk factor for ED remains controversial. Proponents argue that HUA contributes to ED through endothelial dysfunction, which is driven by oxidative stress and inflammation resulting from elevated uric acid levels. The mechanism by which HUA promotes reactive oxygen species (ROS) release may be attributed to increased purine levels in the body enhancing xanthine oxidase (XO) activity, which not only promotes uric acid production but also releases superoxide anions, thereby coupling uric acid formation with ROS release.6 Additionally, HUA activates the local renin–angiotensin system (RAS), upregulating Ang II gene expression and consequently increasing ROS levels.7 HUA also promotes ROS generation by activating the catalytic subunit 2 of nicotinamide adenine nucleotide phosphate (NADPH) oxidase, which produces peroxides through electron transfer.8 Furthermore, HUA can activate the sodium–calcium exchanger (NCX_mito) in endothelial cells, driving calcium ions (Ca²⁺) into mitochondria and increasing ROS levels.9 The detrimental effects of ROS on penile erectile function are primarily associated with oxidative stress in endothelial cells, disruption of skin-derived factors, decreased nitric oxide (NO) concentrations, relatively increased endothelin-1 (ET-1) expression, prolonged contraction of penile blood vessels, impaired blood flow, and congestion in penile tissues, ultimately leading to the onset of ED. This pathological process interferes with NO signaling, promotes vascular smooth muscle proliferation, and results in small vessel disease and microcirculation disorders in the penis.10,11 This pathological process interferes with NO signaling, promotes vascular smooth muscle proliferation, and leads to small vessel disease and microcirculation disorders in the penis. Consequently, it is hypothesized that HUA and ED are pathophysiologically interconnected, with elevated uric acid levels potentially exacerbating endothelial dysfunction and contributing to impaired erectile function.12,13,14 Moreover, HUA can compromise the structure and function of Leydig cells by releasing ROS, which affects androgen synthesis and release. This process inhibits the androgen-driven activation of the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/endothelial nitric oxide synthase (eNOS)/NO pathway, contributing to male hypogonadism and promoting ED.15,16,17

Conversely, opponents argue that the association between HUA and endothelial dysfunction may stem from systemic metabolic disorders rather than HUA being an independent risk factor. Patients with ED who have HUA are more likely to experience metabolic disorders, including diabetes, hypertension, obesity, and hyperlipidemia, which together constitute metabolic syndrome. Consequently, the observed relationship between HUA and endothelial dysfunction may be mediated by these interconnected metabolic disorders rather than by HUA in isolation.18,19,20,21,22 The risk of ED in adult men with metabolic syndrome is nearly twice that of men without it, potentially due to the influence of shared risk factors on penile hemodynamics and the systemic vascular bed. These common factors such as insulin resistance, hypertension, and dyslipidemia may exacerbate endothelial dysfunction and impair blood flow, thereby heightening the risk of ED in this population.23,24,25,26,27,28 Among ED patients with HUA, there is a strong correlation between metabolic disorders of blood glucose, elevated triglycerides, and increased low-density lipoprotein cholesterol (LDL-C) with ED. These metabolic abnormalities may further compromise erectile function by affecting NO production in endothelial cells, promoting vascular smooth muscle proliferation, and worsening microcirculatory disorders.29 HUA is not only directly associated with elevated uric acid levels but is also closely linked to insulin resistance and abnormal lipid metabolism. Research has demonstrated a strong relationship between HUA and diminished insulin sensitivity, with insulin resistance being a core feature of metabolic syndrome that may exacerbate endothelial dysfunction and subsequently impact erectile function.30 The relationship between HUA and hypertension is also significant. HUA may induce vasoconstriction and decrease blood flow by activating the local renin–angiotensin system and elevating oxidative stress levels, thereby impacting the blood supply to the penis.31

While the common risk factors associated with metabolic syndrome can partially elucidate the relationship between HUA and ED, an increasing body of evidence suggests that HUA directly influences erectile function through various independent mechanisms. Consequently, this study aims to develop a multivariate linear model to assess the effects of metabolic factors on erectile function in ED patients with HUA, thereby offering valuable clinical insights and references for more effective management and treatment strategies.

PARTICIPANTS AND METHODS

Participants

The study was designed and conducted in accordance with the principles of the Declaration of Helsinki and received approval from the Medical Ethics Committee of Jiangsu Province Hospital of Chinese Medicine (Nanjing, China; Approval No. 2022NL-066-02). All participants were informed and provided written informed consent. This study was a cross-sectional analysis that included 514 patients diagnosed with both ED and HUA. The inclusion criteria were as follows: a diagnosis of both ED and HUA and an age range of 18–60 years. Individuals with a history of drug abuse, mental disorders, or acute illnesses were excluded from the study.

Clinical data collection

The patient’s detailed medical history was obtained, including chronic diseases such as hypertension, diabetes, and heart disease, as well as past medication history. General demographic data, including age, height, weight, body mass index (BMI), smoking history, alcohol consumption history, and IIEF-5 scores, were collected. Blood samples were drawn on the morning of the 2^nd day following a 12-h fasting period, with 5 ml of venous blood collected. Laboratory measurements included alanine aminotransferase (ALT), aspartate aminotransferase (AST), urea, creatinine (Cr), fasting plasma glucose (FPG), uric acid (UA), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), LDL-C, glycated hemoglobin (HbA1c), serum prolactin (PRL), testosterone (T), and estradiol (E2).

Assessment of ED with the 5-item version of the International Index of Erectile Function (IIEF-5)

Patients were provided with a Chinese version of the IIEF-5 questionnaire, which was utilized to assess their erectile function. This scale comprises five items: erectile hardness, frequency of maintaining an erection, ability to maintain an erection, confidence in erection, and sexual satisfaction. The IIEF-5 questions were scored on a 5-point scale, with a maximum score of 25 and a minimum score of 5; higher scores indicate better sexual function. Based on their IIEF-5 scores, patients were categorized into four groups: those with scores between 17 and 21 were classified as having “mild ED”, scores between 12 and 16 indicated “mild to moderate ED”, scores between 8 and 11 were classified as “moderate ED”, and scores between 5 and 7 were labeled as “severe ED”.32

Statistical analyses

Statistical analyses were performed using R version 4.3.1 (R Foundation for Statistical Computing, Vienna, Austria) for descriptive statistics. The normality of the differences was tested using the Kolmogorov–Smirnov test. Multivariable linear regression modeling was implemented in R version 4.3.1. Following data exploration and missing value imputation, logarithmic transformation was applied to mitigate distributional biases. Variables significantly associated with IIEF-5 scores identified through univariate analysis were incorporated into an ordinary least squares (OLS) regression model, which simultaneously adjusted for interaction effects among metabolic parameters and confounding factors. The step Akaike Information Criterion (AIC) function was used for stepwise regression to optimized model structure. Goodness-of-fit was assessed using adjusted R², F-test, and analysis of variance (ANOVA), while 10-fold cross-validation evaluated model stability. Residual analysis confirmed adherence to linear regression assumptions. The statistical significance was set at P < 0.05.

RESULTS

This study included a total of 514 ED patients with hyperuricemia. The median (interquartile range [IQR]) age of participants was 31 (27–35) years, and all individuals met the inclusion criteria. The median (IQR) fasting serum UA level was 475.00 (444.75–508.00) µmol l⁻¹. The median (IQR) IIEF-5 score was 13 (9–16). Within the patient cohort, 112 (21.8%) exhibited mild ED, 208 (40.5%) demonstrated mild-to-moderate ED, 82 (16.0%) had moderate ED, and 112 (21.8%) were classified as having severe ED, indicating that mild-to-moderate ED was prevalent among the study population. Among the 514 ED patients with HUA, 18 had diabetes, 63 had hypertension, 161 had hyperlipidemia, and 166 were classified as obese. Detailed demographic characteristics, laboratory data, and IIEF-5 scores for the study population are presented in Table 1.

Table 1.

Basic characteristics, laboratory data, and IIEF-5 scores of the study population

Characteristic	All patients (n=514)
Age (year)	31 (27–35)
BMI (kg m−2)	26.12 (23.89–28.72)
Smoking history, n (%)	134 (26.1)
Drinking history, n (%)	138 (26.8)
IIEF-5 score, median (IQR)	13 (9–16)
Mild ED (17–21 points), n (%)	112 (21.8)
Mild to moderate ED (12–16 points), n (%)	208 (40.4)
Moderate ED (8–11 points), n (%)	82 (16.0)
Severe ED (5–7 points), n (%)	112 (21.8)
Laboratory findings at admission
ALT (U l−1), median (IQR)	28 (18–42)
AST (U l−1), median (IQR)	20 (17–27)
Urea (mmol l−1), median (IQR)	4.9 (4.3–5.6)
Creatinine (µmol l−1), median (IQR)	78 (70–84)
Fasting plasma glucose (mmol l−1), median (IQR)	4.63 (4.37–5.03)
UA (µmol l−1), median (IQR)	475.00 (444.75–508.00)
TC (mmol l−1), median (IQR)	4.57 (4.00–5.24)
TG (mmol l−1), median (IQR)	1.63 (1.19–2.39)
HDL-C (mmol l−1), median (IQR)	0.99 (0.86–1.12)
LDL-C (mmol l−1), median (IQR)	2.98 (2.41–3.55)
HbA1c (%), median (IQR)	5.50 (5.30–5.73)
PRL (ng ml−1), median (IQR)	19.36 (15.23–24.89)
Testosterone (ng dl−1), median (IQR)	374.4 (299.52–472.32)
Estradiol (ng l−1), mean±s.d.	30.58±10.09
Comorbidities, n (%)
Hypertension	63 (12.3)
Diabetes	18 (3.5)
Hyperlipidemia	161 (31.3)
Obesity	166 (32.3)

IIEF-5: 5-item version of the International Index of Erectile Function; ED: erectile dysfunction; IQR: interquartile range; s.d.: standard deviation; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; ALT: alanine aminotransferase; AST: aspartate aminotransferase; UA: uric acid; TG: triglyceride; TC: total cholesterol; PRL: prolactin; HbA1c: glycated hemoglobin

In this study, we employed a multivariate linear regression model to investigate the relationships between various metabolic parameters and IIEF-5 scores. The univariate analysis identified several factors significantly associated with IIEF-5 scores, including ALT, AST, T, FPG, UA, TG, LDL-C, HbA1c, and smoking history, all of which were included in the subsequent multivariate stepwise linear regression analysis. The relationships between FPG, UA, TC, TG, HDL-C, LDL-C, HbA1c, T, and the IIEF-5 score are visually represented in Figure 1, demonstrating significant correlations between these metabolic and hormonal indicators and erectile function, with the corresponding R values and P values provided. Additionally, the relationship between smoking history and the IIEF-5 score is illustrated in Figure 2, with Mann–Whitney U test and P values provided, further highlighting the impact of smoking on erectile function. The initial model’s goodness-of-fit was indicated by an R² = 0.242. To enhance the model’s performance, stepwise regression was performed using the AIC to select the most suitable variables. In the stepwise regression process, variables such as ALT, AST, and T were excluded from the final model due to their weak association with IIEF-5 scores. The final model included FPG, UA, TG, LDL-C, HbA1c, and smoking history as key predictors. The model coefficients are presented in Table 2 and Supplementary Figure 1 ^{(58KB, tif)} .

Figure 1.

Scatter plots of the relationships between the most pertinent serum variables’ level and IIEF-5 scores. HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; HbA1c: glycated hemoglobin; IIEF-5: 5-item version of the International Index of Erectile Function.

Figure 2.

Violin plot depicting the relationship between smoking history (smoker vs nonsmoker) and IIEF-5 scores. IIEF-5: 5-item version of the International Index of Erectile Function.

Table 2.

Results of the multivariate linear regression analysis of factors influencing the 5-item version of the International Index of Erectile Function scores

Predictor	Coefficient (estimate)	s.e.	t-statistics	P
Intercept	8.455	0.968	8.732	<0.001***
FPG	−0.628	0.158	−3.973	<0.001***
UA	−0.552	0.154	−3.578	0.00038***
TG	−0.088	0.044	−1.987	0.04742*
LDL-C	−0.164	0.074	−2.214	0.02725*
HbA1c	−0.562	0.224	−2.514	0.01223**
Smoking history	−0.074	0.036	−2.094	0.03678*

*P<0.05; **P<0.01; ***P<0.001. HbA1c: glycated hemoglobin; s.e.: standard error; LDL-C: low-density lipoprotein cholesterol; UA: uric acid; TG: triglyceride; FPG: fasting plasma glucose

The analysis of variance (Table 3) revealed that FPG had the most significant impact on IIEF-5 scores (F = 110.78, P < 0.001). UA also showed a significant effect (F = 14.43, P = 0.00016). Additionally, TC significantly influenced IIEF-5 scores (F = 10.87, P = 0.00105). HbA1c was also found to have a moderate but significant effect (F = 6.47, P = 0.01127). Smoking history showed a borderline significant association with IIEF-5 scores (F = 4.00, P = 0.04603). The final model achieved an AIC value of −1078.94, which is lower than the initial model’s AIC value of −1060.96, indicating a better fit. The multiple R² for the final model was 0.239. During the stepwise regression process, variables such as ALT, AST, and T were excluded, suggesting that these factors were not significant predictors of IIEF-5 scores when other variables were considered. Residual analysis of the final model demonstrated that the residuals were approximately normally distributed, confirming the validity of the model’s assumptions and supporting its goodness-of-fit. The residual plot is shown in Supplementary Figure 2 ^{(54.7KB, tif)} . To assess the model’s stability, a 10-fold cross-validation was conducted, and the results indicated that the model’s predictive performance remained consistent across different training sets, further supporting its reliability, as illustrated in Supplementary Figure 3 ^{(43.2KB, tif)} .

Table 3.

Impact of significant variables on the 5-item version of the International Index of Erectile Function scores (analysis of variance)

Variable	Sum square	Mean square	F	P
FPG	13.612	13.612	110.782	<0.001***
UA	1.773	1.773	14.432	0.00016***
TC	1.335	1.335	10.868	0.00105**
HbA1c	0.795	0.795	6.470	0.01127*
Smoking history	0.492	0.492	4.000	0.04603*

*P<0.05; ^**P<0.01; ^***P<0.001. HbA1c: glycated hemoglobin; UA: uric acid; TC: total cholesterol; FPG: fasting plasma glucose

This correlation suggests that these metabolic abnormalities may play a crucial role in the development of ED. Furthermore, patients with HUA exhibited a more compromised metabolic status, which was associated with more severe ED.

DISCUSSION

This study offers valuable insights into the relationships between metabolic parameters and ED in patients with HUA. By employing multiple linear regression analysis, we identified a linear relationship between the dependent variable, the IIEF-5 scores, and the independent variables, which include FPG, UA, TG, LDL-C, HbA1c, and smoking history. These independent variables emerged as key predictors that are negatively associated with erectile function. This finding highlights the multifactorial nature of ED in patients with HUA, emphasizing the central role of metabolic disorders.

In recent years, the relationship between metabolic syndrome and ED has attracted increasing attention. Research indicates that HUA, a significant component of metabolic syndrome, is closely linked to endothelial dysfunction, oxidative stress, and inflammatory responses, all of which may contribute to the development of ED. Specifically, HUA affects endothelial cell function through various mechanisms, including the increased release of ROS, which leads to a reduction in the production of endothelial NO, a crucial regulator of normal erectile function.33 HUA is associated with the proliferation of vascular smooth muscle and microvascular dysfunction, which further exacerbates the risk of ED. Elevated UA levels not only promote the production of ROS but also act as a critical trigger for the body’s inflammatory response, with inflammatory factors exerting destructive effects on vascular endothelial cells.34,35 UA can stimulate monocytes to release inflammatory cytokines, such as tumor necrosis factor-gamma (TNF-γ) , initiating a systemic aseptic inflammatory response.36 Elevated UA concentrations can activate the p38 and extracellular signal-regulated kinase 44 (ERK44)/42 mitogen-activated protein kinases (MAPK) signaling pathways, leading endothelial cells to release C-reactive protein (CRP), inhibit cell proliferation, and induce endothelial cell damage.37 HUA activates nuclear factor kappa B, promotes monocyte adhesion to endothelial cells, triggers a cascade of inflammatory reactions, and disrupts the structure and function of vascular endothelial cells.38 Additionally, UA can induce oxidative stress and inflammation by activating the high mobility group box chromosomal protein 1 (HMGB1)/receptor for advanced glycation end products (RAGE) signaling pathway, further contributing to endothelial dysfunction.39 Certain inflammatory cytokines also promote ROS release; for example, TNF-α can activate caspase-8 to produce ROS,40 and IL-1β releases ROS through autocrine mechanisms.41 These cytokines exert direct cytotoxic effects on endothelial cells, leading to dysfunction in penile endothelial cells, impaired penile microcirculation, and adverse effects on erectile function.

The stepwise regression analysis conducted in this study revealed that certain variables traditionally deemed significant, such as ALT, AST, and T, were not significant predictors of ED when assessed alongside other metabolic factors. This finding suggests that while these variables may play a role in the broader context of metabolic health, their direct influence on erectile function may be limited or overshadowed by more dominant factors, such as glucose metabolism and lipid profiles. The R² = 0.239 indicates that although the model accounted for a notable portion of the variance in IIEF-5 scores, other unmeasured factors likely contributed to ED within this population. Potential contributors could include psychosocial factors, genetic predispositions, or additional metabolic disturbances not addressed in this study. Furthermore, the modest R² value underscores the complexity of ED as a clinical condition, suggesting that multiple overlapping pathways may be involved.

One of the most pressing areas for future research is to explore the precise mechanisms through which these metabolic parameters influence erectile function. For instance, elevated levels of blood glucose and UA can lead to ED by impairing the production of endothelial NO and compromising the function of vascular smooth muscle.20,26,42 Understanding the role of insulin resistance in ED could pave the way for new therapeutic interventions, particularly for populations at high risk for both diabetes and HUA. Our findings support these emerging perspectives, highlighting the critical role of parameters such as blood glucose, lipid profiles, and UA levels in the pathophysiology of ED. Consequently, UA levels, as an indicator of metabolic health, should be regarded as a significant factor in the monitoring and management of ED. Furthermore, exploring the effects of early interventions through lifestyle modifications or pharmacological treatments aimed at normalizing metabolic indices could yield valuable insights into the prevention and management of ED in HUA patients. From a clinical standpoint, our findings suggest that a comprehensive approach to managing metabolic health should be prioritized in patients with HUA, not only to mitigate cardiovascular and renal complications but also to preserve sexual function.43 Clinicians should consider regular screening for ED in patients with metabolic disturbances and offer early interventions that target these underlying risk factors.

The primary objective of previous studies was to investigate the association between UA levels and ED, often including a substantial number of completely healthy individuals. In contrast to these earlier investigations, the present study concentrated on the relationship between UA levels, other metabolic parameters, and ED through multiple regression analysis within the context of metabolic disorders. Furthermore, the stepwise regression method was employed to optimize the model, ensuring the retention of the most significant variables. Our findings indicated that in patients with HUA, increased UA levels were significantly negatively correlated with the severity of ED. This result suggests that HUA is a potential risk factor for ED, with elevated serum uric acid levels potentially exacerbating ED severity. Consequently, this study offers a novel evaluation framework for understanding the relationship between HUA and ED, providing valuable data to support clinical management and personalized treatment strategies.

This study has several limitations. Its cross-sectional design restricts a comprehensive analysis of how specific metabolic parameters influence erectile function through potential physiological mechanisms, thereby limiting the applicability of the findings in clinical practice. Furthermore, the representativeness of the sample was affected by factors such as geographic location and age, which may impact the generalizability of the results. Lifestyle factors, including physical activity and dietary habits, were not systematically recorded, presenting potential confounders. Future studies should aim to control for these factors to more accurately isolate the effects of metabolic parameters on ED. Additionally, the subjective nature of the IIEF-5 scores may not fully capture the complexity of erectile function. Consequently, further longitudinal research is necessary to elucidate the intricate interactions between metabolic parameters and ED, investigate the underlying mechanisms of these associations, and assess their implications for clinical diagnosis and treatment.

CONCLUSIONS

In summary, this study contributes to the growing body of evidence linking metabolic health with erectile function, emphasizing the critical role of metabolic disturbances in the development and progression of ED among patients with HUA. The findings highlight the importance of adopting an integrated approach to managing HUA and its associated metabolic abnormalities. By addressing these factors, we may improve not only the overall health and quality of life of patients but also their sexual well-being. Clinicians should prioritize the regular monitoring and management of metabolic parameters in patients with HUA as part of a holistic strategy aimed at enhancing both sexual health and general well-being.

AUTHOR CONTRIBUTIONS

JHC and YC designed the experiments. GWD, ZXY, XHZ, JCH, TL, YX, JHC, and YC contributed to clinical data collection and assessment. GWD, JHC, PNN, and ZXY analyzed the results and wrote the manuscript. All authors read and approved the final manuscript.

COMPETING INTERESTS

All authors declared no competing interests.

Supplementary Figure 1

Regression model coefficient: influence degree of significant variables on IIEF-5 score. HDL-C: high-density lipoprotein cholesterol; HbA1c: glycated hemoglobin; IIEF-5: International Index of Erectile Function-5.

Supplementary Figure 2

The left panels showed residuals against fitted values. The right panels show a Q-Q plot to check residual normality and a “residuals vs leverage” plot.

Supplementary Figure 3

The 10-fold cross-validation results (prediction error evaluation of the erectile dysfunction model in hyperuricemia patients).