Male infertility (MIF) refers the failure to achieve pregnancy after 12 months of regular unprotected sexual intercourse due to male factors. It troubles 10–20% of couples worldwide and contribute tremendous obstacles to social and economic progress (1, 2). Meanwhile, as the concentration and quality of male sperm continue to decline, more and more couples will be troubled (1, 3). There are many reasons for MIF, including congenital, acquired, idiopathic, or environmental factors, such as fragmented sperm DNA, which can not only affect the quality of sperm and lead to infertility but also promote recurrent miscarriage or recurrent implantation failure in female partners, according to the latest research (4–6). However, despite extensive research, little is known about the exact mechanism of MIF (1, 3), which poses a great challenge for developing effective treatment methods.

Circulating lipids are a collective term for apolipoprotein A (APOA), apolipoprotein B (APOB), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides in the blood, which have complex and unclear relationship with male fertility. Cholesterol, as the main substrate for steroid synthesis, has shown a crucial role in steroid hormone generation and relates to downstream effects (including spermatogenesis, empowerment, and penetration of the zona pellucida to fertilize oocytes) (7–9). Its content in the sperm membrane is directly related to normal sperm morphology and fertility, indicating that circulating lipids might have protective effects on MIF. This has been confirmed in some observational studies (10, 11) but more studies reported opposite conclusions (12–14), and the causal relationship between circulating lipids and the risk of MIF has not been fully determined.

Statins are the most commonly used lipid-lowering drugs and are widely used in cardiovascular diseases. It has been reported that statins can improve fertility by correcting lipid metabolism disorders through various molecular pathways; however, other studies revealed that statins led to MIF by impairing semen quality and decreasing gonadal function (15–17); in addition, some authors reported statins have no impact on male fertility (18, 19). Thus, the causal relationship between lipid-lowering drugs and MIF risk remains uncertain. It is well known that the treatment of male infertility depends on the development of new drugs, and the important path of new drug development is the reuse of drugs, as this can reduce the cost of new drug research and greatly accelerate the usually lengthy approval process. In addition, as the increasing use of lipid-lowering drugs and new lipid-lowering drugs, it is necessary to elucidate the specific causal relationship between lipid-lowering drugs and MIF risks.

Vitamin D is an endogenous hormone related to human health (20, 21). Previous studies have shown that vitamin D has a significant protective effect on MIF. Interestingly, statins can affect serum vitamin D levels and are considered one of the causes of adverse reactions to statins (22, 23), and vitamin D supplements have been shown to have a synergistic effect with statins, effectively alleviating adverse reactions (24, 25). Indicating that serum vitamin D levels may play a crucial role in the impact of lipid-lowering drugs on MIF. However, there is currently a lack of relevant research.

In recent years, Mendelian randomization (MR) analysis has become a popular and effective causal reasoning method. It uses genetic variations (single nucleotide polymorphisms, SNPs) as instrumental variables (IV) to infer causal relationships between outcomes and exposure, effectively avoiding confounding biases in traditional epidemiological studies and providing a valuable alternative to randomized clinical trials (26). MR analysis of drug targets is a method of simulating genetic variations in pharmacological inhibition (enhancement) of drug-gene targets. The regression estimates obtained from this analysis reflect the long-term effects of drug use, can be used to infer the causal relationship between drug use and disease (27).

This study provides convincing evidence supporting the association of LDLR activator, LPL activator, and CETP inhibitor with higher MIF risk, while HMGCR inhibitor with lower MIF risk; suggesting that LDLR, LPL, CETP, and HMGCR may be potential targets for preventing MIF. Moreover, the increased or reduced risk seemed not to LDL-C or TG control, as no clear evidence suggested a general impact of lipid traits on MIF risk. In addition, the study confirmed the robustness of the results through detailed heterogeneity and sensitivity analysis methods. Intermediary analysis indicated the mechanisms of LDLR activator, LPL activator, and CETP inhibitor on MIF partially by regulating serum vitamin D levels.

Cholesterol is the main source of sex steroid hormone synthesis and plays a decisive role in steroid production and spermatogenesis (8, 9). Animal studies have shown a correlation between cholesterol or steroid production and male fertility (35), however, these animal-model-based evidence do not seem to apply to humans considering complex relationship between lipids and sperm production. In our study, there is no evidence supporting the association between lipid characteristics (LDL-C, HDL-C, TG, Apo-A1, and Apo-B) and MIF risk, this is consistent with views of Neergaard (36) and Osadchuk (37) whom believes that lipid levels in seminal plasma are positively correlated with sperm quality rather than lipid levels. Lipids in seminal plasma may not originate from the blood but from the epithelial cells of male reproductive tract (36). In addition, enzymes involved in cholesterol metabolism in human reproductive tract, testicular interstitial cells, supporting cells, and mature germ cells can self-regulate local cholesterol levels (36). Therefore, lipid characteristics are unlikely to affect sperm quality. However, some studies reported opposite conclusions (10–14) that blood lipid levels were correlated to sperm quality, although some shortcomings may lead to false positive results. Firstly, participants selection is likely biased rather than random, especially in cross-sectional designs. Secondly, these populations seek medical attention due to fertility-related issues, which affects the reliability of the results. Finally, the lack of important information further affects the reliability of the results, such as exercise habits, dietary patterns, and family history.

The relationship between lipid-lowering drugs and MIF mainly focuses on statins. Statins can effectively reduce the level of LDL-C by inhibiting activity of HMG-CoA reductase (38). Our analysis confirms for the first time that HMGCR inhibitors and HMGCR gene expression levels are associated with lower MIF risk. This seems to be unrelated to the lipid-lowering ability of HMGCR inhibitors, as we did not observe any association between lipid characteristics and male infertility, indicating that other factors mediate this positive effect. HMGCR inhibitors have shown ability to reduce production of inflammatory mediators and cytokines to alleviate inflammatory responses (39, 40). These effects may relate to the protective effect of HMGCR inhibitors, as it found that male infertility patients typically had elevated levels of certain inflammatory markers, such as C-reactive protein, interleukin-6, and tumor necrosis factor-α. This might indicate a potential systemic inflammatory state (37, 38). In addition, previous studies have shown that statins can inhibit oxidant-induced reactive oxygen species (ROS) (41, 42). The increased ROS can lead sperm dysfunction as well as abnormalities in sperm quantity, motility, and morphology (43). Meanwhile, the imperfect antioxidant mechanism of sperm makes them particularly sensitive to damages induced by excessive ROS (44). However, previous observational studies have almost reported the negative effects of statins (16–19). Although Yan (45) confirmed a correlation between HMGCR inhibitors and lower serum testosterone levels (including total testosterone and bioavailable testosterone), this did not mean that it could lead abnormal semen quality or even MIF. There is no clear relationship between testosterone and function, nor between serum testosterone levels and semen parameters (46, 47). On the contrary, the abuse of exogenous androgens can lead to MIF (48). Therefore, we speculated that this negative impact may be related to reverse causality and residual confounding effects, as well as upregulation of LDLR and LPL expression or activity.

LDLR, as an indirect target of statins, increases in activity and expression with HMGCR inhibition (49). We also firstly confirmed that LDLR activators were associated with higher risk of MIF. LDLR is a key cell surface receptor for cholesterol uptake and transport, which regulating the homeostasis of plasma and cellular cholesterol by mediating the up-taking and metabolism of plasma-derived LDL-C (49). It is related to the process of sperm production (36, 50, 51). Research has found that heterozygous deletion of LDLR reduced cholesterol toxicity in the testes of hamsters and improved the reproductive ability of male hamsters, indicating the presence of sufficient cholesterol and increased LDR level led the accumulation of cholesterol in the testes, which finally inducing testicular toxicity. This suggests that LDLR may regulate cholesterol metabolism and stability in the reproductive system (50). This has also been confirmed in the study by Pelletier et al. (51), who found that when the upstream inhibitor of LDLR (PCSK9) was missing, the increased LDLR contributed excessive accumulation of testicular cholesterol to affect metabolic stability and immune tolerance in the seminiferous tubules, and finally impairing mice fertility. Similarly, statin drugs have been reported to increase the expression level and activity of LPL (52), our study also showed that LPL activators were associated with higher MIF risk, indicating that LPL might be involved in the negative effects of statins. However, no research has focused on the relationship between LPL and MIF. We speculated that it was related to the stable imbalance of fatty acid metabolism in reproductive tract tissues. Firstly, LPL is a key enzyme in lipid metabolism. As a gatekeeper of tissue fatty acid uptake (53), it is widely expressed in male reproductive tissues (36). Upregulation of LPL activity and expression will lead increased breakdown of triglycerides, production of more free fatty acids, and entry into reproductive tract tissues, leading to the accumulation of free fatty acids and activation of inflammatory pathways (53), which will further affect sperm quality (54). However, other studies involving in vitro experiments, animal models, and clinical trials are needed to reveal complex molecular pathways and confirm the therapeutic potential of LPL regulation in reducing MIF.

Vitamin D is an endogenous hormone that associates to human health (20, 21). Previous studies have shown that statin drugs can affect serum vitamin D level and are considered one of the causes of adverse reactions to statins (22, 23). On the contrary, vitamin D supplements have been shown to have a synergistic effect with statins to effectively alleviate adverse reactions (24, 25). Therefore, the effect of statins on serum vitamin D levels may also be involved in the negative impact on MIF. In our analysis, we found no correlation between HMGCR inhibition and vitamin D levels. LDLR activators and LPL activators were associated with lower serum vitamin D levels, which may be the reason why statins were associated with lower vitamin D levels. However, the increased serum vitamin D level is considered a protective factor for MIF (22). Therefore, we believe that the decreased serum vitamin D may also be involved in the negative effects of statins on MIF.

CETP mediates the bidirectional transfer of cholesterol esters and triglycerides between plasma lipoprotein particles, which receives great attention due to its activity to increase HDL-C (55). However, CETP inhibitors have always been a controversial topic that previous clinical trials reported it increased risk of major coronary heart disease events (56) due to the renin-angiotensin-aldosterone system (RASS) (57), meanwhile, as overactivated RASS system is also associated with MIF (58), some studies suggested that the CETP inhibitors were theoretically increased MIF risk, which is consistent with our current finding. Recently, more attention has been paid on developing new drugs with CETP inhibitors as the core mechanism, indicating exploring the specific mechanisms of CETP and MIF will be of great significance.

Our research provides several advantages. Firstly, this is the first study to explore the causal relationship between lipid traits, lipid modification targets, and MIF. Secondly, we used univariate MR analysis, multivariate MR analysis, and drug target MR analysis to investigate the causal relationship between LDLR activator, LPL activator, CETP inhibitor, HMGCR inhibitor, and MIF, as well as the mediation of serum vitamin D levels to emphasize the necessity of further studying the potential reproductive effects of long-term use of lipid-lowering drugs. Meanwhile, our research also suggests that further research is needed to investigate the relationship between other novel drug targets with synergistic effects with lipid-lowering drugs and MIF, such as TNF - α (59, 60), which possibly further the discovery of novel therapeutic targets for MIF. In addition, the MR design is not easily affected by residual clutter, and the GWAS summary level data in this study has a large sample size, which effectively reduces the confounding factors. Finally, the detailed heterogeneity and multi-validity tests were conducted to confirm the reliability of our results.

However, several limitations also exist. For example, as genetic variations typically originate from parents and are less susceptible to environmental influences, they reflect a lifelong impact on the exposure. Therefore, using genetic variations to study the effects of lipid-lowering drugs is limited, reflecting the long-term effects of lipid-lowering drugs on MIF, which may not be comparable to the short-term effects of lipid-lowering drugs (within a specific time frame). So, the drug MR analysis helps to determine the direction of causal relationships rather than quantifying the degree of correlation. So, RCT research under specific conditions is still necessary. Meanwhile, despite with detailed heterogeneity and pleiotropy tests, the effect of horizontal pleiotropy cannot be completely ruled out. In addition, due to the significant differences in genetic variation among different races and the fact that our research findings are mainly related to individuals of European ancestry, these findings may not necessarily apply to other ethnic groups. Therefore, it is necessary to conduct cross racial analysis when appropriate GWAS data is available. Finally, despite the large sample size, the original GWAS data was not stratified according to certain subtypes (MIF caused by sperm quality, MIF caused by testicular disease, and obstructive MIF, etc.), therefore, this study was unable to conduct stratified analysis. It remains a research topic and should be considered when specific datasets are available in the future.

This study does not support lipid traits (LDL-C, HDL-C, TG, Apo-A1, and Apo-B) as pathogenic risk factors for MIF. However, it emphasizes that LPL, LDLR, CETP, and HMGCR are promising drug targets for improving male fertility. The underlying mechanisms should be elucidated in further research, and the role of LPL activators, LDRL activators, CETP inhibitors, and HMGCR inhibitors in MIF in basic or even clinical trials might be worth assessing. However, the findings in this study require a larger GWAS dataset with a more complete phenotype, as well as other potentially relevant genetic variations, to validate.

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

WL: Conceptualization, Data curation, Methodology, Supervision, Writing – original draft, Writing – review & editing. BC: Conceptualization, Investigation, Methodology, Writing – original draft. HL: Data curation, Formal analysis, Validation, Visualization, Writing – original draft, Writing – review & editing. CZ: Investigation, Writing – original draft. YY: Conceptualization, Writing – review & editing. JY: Investigation, Project administration, Writing – original draft. TL: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.