Causal relationship between immune cells, inflammatory cytokines, metabolites, and erectile dysfunction: a two-sample Mendelian randomization study

Introduction

Erectile dysfunction (ED) is a common male sexual disorder characterized by the inability to achieve or maintain an erection sufficient for satisfactory sexual performance (1). This process relies on the intricate coordination of the neurological, endocrine, vascular, and corporal systems, involving neurotransmitter release, arterial inflow, smooth muscle relaxation in the corpora cavernosa, and venous occlusion (2). ED often coexists with comorbidities such as hypertension (40%), hyperlipidemia (42%), and diabetes (20%), as well as neurological, endocrine, and psychological disorders (1,3). As the global population ages, ED has become an increasingly prevalent issue, significantly affecting men’s quality of life and mental health. Statistics show that about two-thirds of men worldwide experience varying degrees of ED, with the prevalence continuing to rise (4).

Despite the high prevalence of ED, its precise mechanisms remain incompletely understood. ED can be broadly categorized into three types based on its etiology: organic, psychogenic, and mixed. Organic ED is further subdivided into vascular, neurogenic, anatomical, and endocrine types (5). Historically, ED was attributed to psychological factors such as anxiety, depression, and personality traits (6). However, advancing research indicates that ED functions as a vascular disease, with various bioactive substances in the bloodstream playing crucial roles in its onset and progression (7). Studies suggest that ED is closely associated with physiological factors including immune inflammatory responses, metabolic disorders, and hormonal imbalances (8,9). Recent research has found that the immune system induces the production of pro-inflammatory cytokines through Toll-like receptors (TLRs), leading to tissue infiltration by immune cells and creating an inflammatory environment. This process promotes vascular damage and contributes to ED development (10). Additionally, various metabolites play significant roles in the onset and progression of ED. Factors such as abnormal lipid metabolism, diabetes, and metabolic syndrome are risk factors for ED (11).

Given the critical roles of the immune system, inflammatory cytokines, and metabolites in maintaining vascular homeostasis and function, research increasingly focused on their potential associations with ED. Previous studies have established a close relationship among the three factors related to ED, yet few have investigated the causal relationships between them (12,13). Traditional studies often face limitations, such as small sample sizes and a lack of randomization, which can compromise their credibility. Mendelian randomization (MR) is an effective method that employs genetic variants associated with exposure as instrumental variables (IVs) to ascertain the causal relationship between exposure and outcome. It mimics the randomization process found in natural environments or randomized controlled trials (RCTs), significantly enhancing the reliability of the research (14). The fixed nature of genetic variants, which are randomly allocated at conception and relatively unaffected by environmental factors, allows MR to yield unbiased estimates of causal relationships (15). In this study, we aim to assess causal relationships between immune cells, inflammatory proteins, and plasma metabolites with ED using data from genome-wide association studies (GWAS). The data from this study might provide new theoretical insights into the pathophysiological mechanisms and therapeutic strategies for ED. We present this article in accordance with the STROBE-MR reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-24-395/rc).

Methods

Ethical statement

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Study design

As depicted in Figure 1, this study comprises two main parts: The first part analyzed the causal relationships between 731 immune cells, 91 inflammatory cytokines, 1,400 metabolites and the risk of ED. The second part used factors identified in the first part with causal relationships to ED as outcomes, with ED as the exposure variable, employing reverse MR to eliminate potential reverse causation (Figure 1). In this study, single nucleotide polymorphisms (SNPs) are defined as IVs, and the main results were presented in the article and its supplementary materials.

Figure 1 Schematic of the study design in this MR analysis. The figure was created by Figdraw (https://www.figdraw.com/). GWAS, genome-wide association studies; IEU, Integrative Epidemiology Unit; ED, erectile dysfunction; MR, Mendelian randomization.

Selection of IVs

Firstly, we extracted SNPs associated with exposure from summary data of GWAS. Given the limited number of IVs at a significance level of 5×10⁻⁸, we relaxed the significance threshold for the three exposures (immune cells, inflammatory cytokines, metabolites) to 5×10⁻⁶ to ensure sensitivity analysis could be conducted. Secondly, to mitigate the effects of linkage disequilibrium, we set thresholds at r²<0.001 and distance less than 10,000 kb (16). Additionally, we excluded palindromic SNPs and removed IVs correlated with outcomes. Finally, we determined the variance explained by each SNP’s R² value for the exposure and assessed instrument strength using the F-statistic (F>10) to mitigate potential issues associated with weak instruments (17).

Data sources

The data used in the present study are publicly available, and participants in the GWAS are of European descent. ED data were sourced from the Integrative Epidemiology Unit (IEU) Open GWAS with accession number ebi-a-GCST006956 (18). ED was defined as either self-reported or physician-reported, using International Classification of Diseases, 10th revision (ICD-10) codes N48.4 and F52.2; the use of oral ED medications (sildenafil, tadalafil, or vardenafil); or a history of surgical intervention for ED [Office of Population Censuses and Surveys Classification of Surgical Operations and Procedures version 4 (OPCS-4) codes L97.1 and N32.6] (18). This comprehensive study recruited 223,805 European males (6,175 cases and 217,630 controls) from the Partners HealthCare Biobank cohort, UK Biobank cohort, and the Estonian Genome Center at the University of Tartu. Our study utilized three types of exposure data. Data on 1,400 plasma metabolites were sourced from the European GWAS with accession numbers GCST90199621 to GCST90201020. These data encompass 1,091 blood metabolites and 309 metabolite ratios (19). The summary statistics for 91 circulating inflammatory cytokines were obtained from the latest GWAS conducted by the SCALLOP consortium (20). This GWAS involved genome-wide association analysis of genetic variations in 91 inflammatory cytokines, comprising 14,824 individuals of European ancestry (accession numbers GCST90274758-GCST90274848) (20). The GWAS data for 731 immune phenotypes (accession numbers GCST0001391-GCST0002121) involve a study of 6,620 individuals of Sardinian ancestry and 746,667 individuals from five different global populations of European descent (21). The data encompass 118 absolute cell counts, 389 median fluorescence intensities representing surface antigen levels, 32 morphological features, and 192 relative cell counts. The study design, including sample collection, quality control procedures, and imputation methods, has been described in the original publication.

Statistical analysis

All statistical analyses were conducted using R 4.3.1 (https://www.r-project.org/). The ‘TwoSampleMR’ package was used for two-sample MR analyses. In MR, the inverse variance weighted (IVW) method (22), MR-Egger method (23), Simple mode method, weighted median method, and weighted mode method were utilized. IVW was the primary method for causal estimation due to its precision and robustness. A significance level of P<0.01 (24) and consistent direction of effects across all five methods (β direction) were considered indicative of a significant association between exposure and outcome. The MR-Egger method used regression intercepts to test for potential pleiotropy effects. Cochran’s Q statistic was used to assess heterogeneity in the analysis (25). The MR-PRESSO analysis method aims to detect and correct for horizontal pleiotropy (26). If heterogeneity was present, a random-effects IVW model was applied; otherwise, a fixed-effects IVW model was used (27).

Results

Causal relationships between immune cells and ED

Our MR study identified causal relationships between five immune cell phenotypes out of 731 examined and ED. Specifically, CD19 on immunoglobulin D⁻ (IgD⁻) CD38⁺ B cells [odds ratio (OR) =1.17; 95% confidence interval (CI): 1.06–1.30], CD4 on terminally differentiated CD4⁺ T cells (OR =1.07; 95% CI: 1.02–1.12), CD25 on IgD⁺ CD38dim B cells (OR =1.05; 95% CI: 1.01–1.09), and CD25 on IgD⁺ CD24⁻ B cells (OR =1.04; 95% CI: 1.01–1.07) showed statistically significant associations with increased risk of ED. Conversely, IgD on IgD⁺ B cells (OR =0.88; 95% CI: 0.79–0.97) exhibited a negative correlation with ED, suggesting a protective effect. Additionally, Cochran’s Q test, MR-Egger intercept test, and MR-PRESSO were used to evaluate heterogeneity and horizontal pleiotropy.

Causal relationships between inflammatory cytokines and ED

MR analysis of 91 inflammatory proteins, using the IVW method, revealed that only one protein, urokinase-type plasminogen activator (uPA), showed a negative correlation with ED (OR =0.83; 95% CI: 0.73–0.95). Additionally, heterogeneity and horizontal pleiotropy were evaluated using Cochran’s Q test, MR-Egger intercept test, and MR-PRESSO. No statistically significant associations were found for the remaining inflammatory cytokines.

Causal relationships between metabolites and ED

We identified potential associations between ED and two blood metabolites and four metabolite ratios (P<0.01). In the assessment of blood metabolites, our study found positive associations between glycerol levels (OR =1.30; 95% CI: 1.08–1.56) and X-16964 levels (OR =1.24; 95% CI: 1.06–1.45) with ED. Regarding metabolite ratios, the study results included positive associations for the aspartate to N-acetylglucosamine to N-acetylgalactosamine ratio (OR =1.21; 95% CI: 1.07–1.37), cholesterol to taurocholate ratio (OR =1.23; 95% CI: 1.07–1.42), and 4-methyl-2-oxopentanoate to 3-methyl-2-oxobutyrate ratio (OR =1.26; 95% CI: 1.07–1.48) with increased risk of ED. Conversely, the alpha-ketoglutarate to kynurenine ratio (OR =0.86; 95% CI: 0.76–0.96) showed a negative correlation with ED. The results from MR-Egger, Cochran’s Q test, and MR-PRESSO indicated no significant horizontal pleiotropy or heterogeneity. Details of the statistical methods and additional data are provided in Figures 2,3, as well as tables available at https://cdn.amegroups.cn/static/public/TAU-24-395-1.xlsx and https://cdn.amegroups.cn/static/public/TAU-24-395-2.xlsx.

Figure 2 Forest plot of causal relationships between immune cells, inflammatory cytokines, metabolites, and ED. This figure presents the results of the IVW analysis, indicating associations between six plasma metabolites, five immune cells, and one inflammatory cytokine with ED. The OR, 95% CI, and P value for each association are provided. SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted; IgD, immunoglobulin D; ED, erectile dysfunction.

Figure 3 The circular heatmap illustrates reverse MR between phenotypes with a causal relationship to ED. The outer ring displays the names of the 12 phenotypes, while the inner ring uses different colors to represent the P values from various sensitivity analyses. The results indicate no significant statistical differences. IVW, inverse variance weighted; MR, Mendelian randomization; pval, P value; IgD, immunoglobulin D; ED, erectile dysfunction.

Discussion

In this MR study, we investigated the potential causal roles of circulating biomarkers related to metabolism, inflammation, and immunity in the development of ED. We identified causal relationships between ED and 12 factors: five immune cells, one inflammatory cytokine, two metabolites, and four metabolite ratios. Rigorous sensitivity analyses confirmed the reliability of our MR results, showing statistical and potential clinical significance. Our findings deepen the understanding of the pathophysiological mechanisms underlying ED and offer new directions for therapeutic interventions targeting these biomarkers. Notably, they provide a foundation for developing personalized treatment strategies to improve the overall health outcomes of ED patients.

The immune system significantly influences ED development (28). B cells, essential components of the adaptive immune system, can be affected by TLR signaling, which is crucial in injuries related to sexual dysfunction (29,30). Our study found that three B cell phenotypes were positively associated with ED risk: CD19 on IgD⁻ CD38⁺ B cells, CD25 on IgD⁺ CD38dim B cells, and CD25 on IgD⁺ CD24⁻ B cells. Additionally, IgD on IgD⁺ B cells showed a negative correlation with ED risk. This suggests that CD19 and CD25 expression in B cells is critical for ED. CD19, an immunoglobulin receptor exclusively expressed on B lymphocytes, is vital for B cell receptor (BCR) signal transduction. It enhances calcium release, protein kinase activation, and cell proliferation (30). Although research on CD19 and ED is limited, one study suggests that CD19 modulates TLR signaling in a scleroderma model, affecting fibrosis and potentially linking to ED (31). Our study found that high CD25 expression in B cells was positively associated with ED risk, possibly due to abnormal immune responses or inflammation affecting erectile function. However, further research is needed. IgD primarily assists B cells in recognizing antigens and regulating survival and activation (32). Our study showed that IgD on IgD⁺ B cells was negatively associated with ED risk, suggesting a protective role. High IgD expression may offer a protective role against ED by reducing inflammation through immune modulation (33). T cells also play a crucial role in the adaptive immune system (34). Our findings showed that CD4 on Terminally Differentiated CD4⁺ T cells was positively associated with ED risk. Terminally Differentiated CD4⁺ T cells, mature T cells that have undergone multiple antigen stimulations and divisions, produce significant cytokines to regulate immune responses (35,36). We speculate that these cells may increase ED risk by promoting chronic inflammation and immune senescence, leading to endothelial dysfunction. These changes could impair vascular health and the ability to maintain erectile function. In clinical practice, immune cell-based therapies have already been employed to treat various immune-related diseases. Notably, Bonanni and colleagues demonstrated the effectiveness of autologous immune cell regenerative therapy in treating vasculogenic ED (37). Our findings may provide crucial theoretical support for the advancement of such therapies, highlighting the significant role of the immune system in ED pathogenesis. Consequently, further investigation into the potential benefits of immune cell-based treatments in the context of ED is essential for future research. By deepening our understanding of the role of immune cells in ED progression, we may pave the way for novel therapeutic strategies to improve male reproductive health and overall quality of life.

A higher systemic immune inflammation index is associated with an increased risk of ED (37). Previous studies have shown that certain inflammatory proteins, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), negatively affect erectile function by modulating cellular signaling pathways (38,39). These findings suggest a potential link between inflammation and erectile function, providing avenues for future research. uPA is a serine protease that activates plasminogen. When uPA binds to its receptor, it converts plasminogen to plasmin on the cell surface and triggers signaling pathways that promote cell migration, proliferation, and survival (40). The plasminogen-plasmin system is also linked to male reproductive function. An animal study showed that downregulation of uPA reduces fertility and sperm motility in male mice, confirming the essential role of uPA as a key factor for normal male fertility (41). Additionally, Autilio et al. found that soluble uPA receptor may serve as a potential marker for inflammation of the male accessory glands (42). Our MR analysis confirmed that uPA has a protective effect against ED, further confirming its potential as a therapeutic direction. Future studies should explore the specific mechanisms by which uPA contributes to ED treatment, potentially paving the way for novel therapeutic approaches that could enhance male sexual function and overall quality of life.

Plasma metabolites are various chemical substances found in plasma, reflecting the body’s metabolic status, including amino acids, lipids, sugars, nucleotides, and other small molecules (43). Studies indicate that plasma metabolites, such as prostaglandin E1, play a crucial role in maintaining erectile function and are key targets for treating ED (44). At the same time, plasma metabolic disorders are a major cause of ED and may negatively affect long-term treatment outcomes (45). A metabolomics study identified 31 metabolites in plasma samples from ED patients and normal controls, among which 8 metabolites, including formate, creatinine, and myo-inositol, were identified as potential biomarkers for ED (45). Glycerol is a crucial biochemical substance and a component of fatty acid esters like triglycerides (46). Elevated glycerol levels may signal metabolic disturbances in adipose tissue, potentially causing vascular endothelial dysfunction, a known factor in vascular ED. Although the direct association between glycerol levels and ED is limited, one study found significant lipid accumulation in the corpora cavernosa of men with ED (47). Our MR results suggested that elevated glycerol levels may increase the risk of ED, further identifying it as a potential therapeutic target for reducing ED incidence. The mechanism of X-16964 remains unclear, however, our MR analysis indicated a positive association with ED. In a clinical study on long bone trauma, Ibrahim found that plasma levels of X-16964 are closely related to inflammatory responses (48). It is plausible to suspect that X-16964 levels may also be elevated due to an inflammatory response during the progression of ED. Additionally, the identification of metabolic ratios offers new insights into ED pathogenesis. In our study, the aspartate to N-acetylglucosamine to N-acetylgalactosamine ratio was positively correlated with an increased risk of ED. Aspartate is a non-essential amino acid involved in biochemical processes such as protein synthesis and the urea cycle (49). A clinical study indicated that a high oral dosage of L-arginine aspartate combined with adenosine monophosphate was effective in treating patients with mild to moderate ED (50). GlcNAc and GalNAc are essential amino sugars involved in glycosylation, a key process in male reproduction (51). Imbalances among these components may disrupt metabolic pathways, suggesting that regulating the relative concentrations of metabolites could be a potential therapy for ED. ED is closely linked to oxidative stress, and alpha-ketoglutarate boosts glutathione biosynthesis, activating the antioxidant system and enhancing resistance to oxidative stress (52). Kynurenine is an intermediate product in the tryptophan metabolism pathway, while another pathway involves serotonin (53). Serotonin enhances male mating behavior and may be useful in treating sexual disorders like ED and hypo-sexuality in men (54). There may be a potential relationship between the two and the occurrence of ED. Our study found that an increased ratio of alpha-ketoglutarate to kynurenine serves as a protective factor for ED. In summary, these findings suggest that these metabolites may serve as potential auxiliary diagnostic markers and tools for assessing prognosis in ED. Moreover, modulating metabolite dependencies and networks through combination therapies represents a new frontier in the treatment of ED.

The advantages of MR studies include the random assignment of subjects, which effectively reduces biases and confounding factors. Furthermore, employing the two-sample bidirectional MR method minimizes the risk of confounding or reverse causality. However, evaluating 1,400 blood metabolites, 731 immune cells, and 91 inflammatory factors presents greater computational demands and introduces complex analytical challenges compared to previous MR analyses involving single exposure factors. However, there are also limitations with MR studies. First, due to the lack of data from other populations, our study only focused on individuals of European ancestry. It may lower the generalizability of other populations such as East Asian, African, Hispanic, etc. Therefore, before applying our results clinically, they should be validated through rigorous RCTs and foundational research, and caution is advised when extending our findings to other racial populations. Second, due to the current sample size, many exposure factors did not reach significance after false discovery rate (FDR) correction. Future studies with larger sample sizes or meta-analyses are needed to identify more factors associated with ED risk. Third, while MR offers statistical inference of causality based on genetic instruments, the causal association between exposure and outcome is only at genetic level. Our results and conclusion could not be directly used to explain the biological mechanism of ED. Further clinical and basic research is needed to explore this in greater depth. Fourth, although we employed MR-PRESSO and MR-Egger regression tests to account for the influence of pleiotropy, there remains a possibility that the inclusion of pleiotropic SNPs in our study may lower the robustness of our results. Lastly, our data were derived from two large-scale GWAS studies and lack detailed demographic, clinical information and basic data of patients, so making subgroup analyses by sex or ED severity is impossible.

Conclusions

In this study, using MR analysis, we identified one inflammatory factor, five immune cell types, and six metabolites associated with ED. These findings offer new avenues for researchers to explore the biological mechanisms underlying ED.

Acknowledgments

The data on erectile dysfunction were provided by Bovijn et al. [2019] and can be accessed through the IEU Open GWAS project (https://gwas.mrcieu.ac.uk/datasets/). The data on immune cells, metabolites, and inflammatory factors were provided by Orrù et al. [2020], Chen et al. [2023], and Zhao et al. [2023], respectively, and were sourced from the GWAS Catalog database. We express our gratitude to the investigators who provided the valuable genetic summary statistics that made this study possible.

Funding: This work was supported by the research grants from the Shaanxi Province Innovation Capability Supporting Program (No. 2024CX-GXPT-39), the Clinical research projects of AFMU (No. 2023LC2301), the National Natural Science Foundation of China (No. 82070973), and the Military Family Planning Special Research Project (No. 24JSZ06).

Footnote

Reporting Checklist: The authors have completed the STROBE-MR reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-24-395/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-24-395/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-24-395/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Since we used public data of GWAS in this study, which has no basic patient information, baseline data and other information, only SNP data of specific phenotypic population are used for research, so ethical review is not required. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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