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The association between testosterone, estradiol, estrogen sulfotransferase and idiopathic pulmonary fibrosis: a bidirectional mendelian randomization study

BMC Pulmonary Medicine volume 24, Article number: 435 (2024) Cite this article

Abstract

Background

The causal relationships between testosterone, estradiol, estrogen sulfotransferase, and idiopathic pulmonary fibrosis (IPF) are not well understood. This study employs a bidirectional two-sample Mendelian Randomization (MR) approach to explore these associations.

Methods

All genetic data utilized in our study were obtained from the IEU Open GWAS project. For the MR analysis, we employed the inverse variance weighted (IVW), MR-Egger, and weighted median methods to assess the causal relationships. We also conducted a multivariate MR (MVMR) analysis, with adjustments made for smoking. To ensure the robustness of our findings, sensitivity analyses were conducted using Cochran’s Q test, MR-Egger regression, the MR-PRESSO global test, and the leave-one-out method.

Results

Genetically predicted increases in serum testosterone levels by one standard deviation were associated with a 58.7% decrease in the risk of developing IPF (OR = 0.413, PIVW=0.029, 95% CI = 0.187 ∼ 0.912), while an increase in serum estrogen sulfotransferase by one standard deviation was associated with a 32.4% increase in risk (OR = 1.324, PIVW=0.006, 95% CI = 1.083 ∼ 1.618). No causal relationship was found between estradiol (OR = 1.094, PIVW=0.735, 95% CI = 0.650 ∼ 1.841) and the risk of IPF. Reverse MR analysis did not reveal any causal relationship between IPF and testosterone (OR = 1.001, PIVW=0.51, 95% CI = 0.998 ∼ 1.004), estradiol (OR = 1.001, PIVW=0.958, 95% CI = 0.982 ∼ 1.019), or estrogen sulfotransferase (OR = 0.975, PIVW=0.251, 95% CI = 0.933 ∼ 1.018). The MVMR analysis demonstrated that the association between testosterone (OR = 0.442, P = 0.037, 95% CI = 0.205 ∼ 0.953) and estrogen sulfotransferase (OR = 1.314, P = 0.001, 95% CI = 1.118 ∼ 1.545) and the risk of IPF persisted even after adjusting for smoking.

Conclusions

Increased serum levels of testosterone are associated with a reduced risk of IPF, while increased levels of serum estrogen sulfotransferase are associated with an increased risk. No causal relationship was found between estradiol and the development of IPF. No causal relationship was identified between IPF and testosterone, estradiol, or estrogen sulfotransferase.

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Introduction

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease characterized by progressive and irreversible pulmonary fibrosis. The etiology and pathogenesis of IPF are complex and not yet fully understood. Risk factors for IPF include aging, smoking history, genetic factors, environmental exposure, lung microbiota, gastroesophageal reflux, and more [1]. It is currently believed that IPF is caused by persistent or repeated lung epithelial injury and subsequent activation of fibroblasts and myofibroblast differentiation [2]. Persistent myofibroblast expression leads to excessive extracellular matrix deposition, abnormal lung repair, tissue scarring, distortion of alveolar structure, and irreversible loss of lung function [2]. According to a study covering 12 countries, the adjusted incidence and prevalence rates of IPF are 0.09–1.2/10,000 and 0.33–4.51/10,000, respectively [3]. IPF predominantly affects males, with a French multicenter prospective study reporting that 78% of 236 newly diagnosed IPF patients were male, and 22% were female [4]. IPF progresses rapidly and has a poor prognosis. A systematic review and meta-analysis of 63,307 patients from 20 countries showed 3-year and 5-year survival rates of 61.8% (95% CI 58.7 ∼ 64.9) and 45.6% (95% CI 41.5 ∼ 49.7), respectively [5].

Currently, FDA-approved drugs for treating IPF include Pirfenidone and Nintedanib, both of which can slow the progression of IPF but cannot reverse established pulmonary fibrosis and are associated with tolerability issues [6, 7]. Lung transplantation remains the best option for treating IPF, but it is plagued by issues such as donor shortage, surgical risks, infection risk, and rejection reactions. Therefore, exploring new treatment approaches for IPF is imperative.

Sex hormones are a class of biological molecules produced by the endocrine system, primarily including androgens and estrogens. Testosterone and estradiol are the most prominent biologically active forms of androgens and estrogens, respectively [8, 9]. Sex hormones play important roles not only in sexual development and reproductive system function but also in influencing the immune system and metabolism. Estrogen sulfotransferase is the enzyme with the highest affinity for estrogens and is primarily responsible for catalyzing the sulfation of estrogens [10, 11]. Estrogen sulfotransferase has also been found to be involved in the sulfation of dehydroepiandrosterone and thyroid hormones [10].

Sex hormones have been found to participate in the fibrotic processes in multiple organs, including the heart, kidneys, liver, and more [12,13,14,15,16]. However, research on the role of sex hormones in IPF is limited, and some results are contradictory. A case-control study involving 101 male IPF patients and 51 healthy controls found a significant decrease in testosterone levels in the IPF group [17]. Furthermore, Nawa H et al. found that anti-androgen drugs might lead to interstitial pneumonia, possibly by inhibiting the binding of androgens to receptors [18]. Regarding estradiol, Smith LC et al. discovered that estradiol may reduce lung fibrosis occurrence by specifically downregulating the expression of Chloride intracellular channel 3 and Retinol binding protein 7, genes associated with IPF, without affecting the transforming growth factor beta1 (TGF-β1) signaling pathway [19]. Xiao YH et al. discovered that estradiol could inhibit the development of lung fibrosis in mice by upregulating the expression of Caveolin-1 and suppressing the expression of type III collagen [20]. In addition, Solopov P et al. reported that dietary phytoestrogen intake could alleviate lung fibrosis in mice [21]. However, Gharaee-Kermani M et al. arrived at different conclusions, finding that female rats had more severe lung fibrotic responses than male rats, ovariectomy reduced lung fibrosis severity, and estradiol replacement therapy restored fibrotic responses, suggesting a potential pro-fibrotic role of estrogens [22]. Tofovic SP et al. demonstrated that estrogen had an anti-mitotic effect on human lung fibroblasts only at high pharmacological concentrations (5µM) and had no effect on the growth of human lung fibroblasts at a concentration of 10µM [23]. In contrast, 2-methoxyestradiol (an endogenous metabolite of estradiol) inhibited the growth of human lung fibroblasts in a concentration-dependent manner [23]. Currently, research on the role of estrogen sulfotransferase in IPF is still lacking. Therefore, further studies are needed to explore the causal relationships between testosterone, estradiol, estrogen sulfotransferase, and IPF.

Mendelian Randomization (MR) analysis is a research method in genetic epidemiology proposed by Professor Katan. The basic principle of MR is to use genetic variation as instrumental variables (IVs) to infer causality between exposure and outcome [24]. Unlike traditional studies that can only discover associations between variables, MR can provide stronger evidence for causal inference. Furthermore, MR’s greatest advantage is that genetic variation is randomly allocated at conception, reducing the possibility of reverse causation and the influence of confounding factors [25]. Compared to observational studies, which are susceptible to bias and confounding factors, and experimental studies, which are costly and subject to ethical limitations and participant compliance issues, MR offers a robust approach for causal inference. MR must satisfy three core assumptions [24]: the relevance assumption, where IVs must be closely related to the exposure; the independence assumption, where IVs are not influenced by potential confounding factors; and the exclusion restriction assumption, where genetic variation affects the outcome only through the exposure (Fig. 1) .

In this study, our data were derived from a genome-wide association study (GWAS), and we employed a two-sample bidirectional MR approach to investigate the causal relationships between testosterone, estradiol, estrogen sulfotransferase, and IPF.

Methods

Study design

We conducted a two-sample MR study to explore the causal relationships between testosterone, estradiol, estrogen sulfotransferase and IPF. Causal effects were assessed using the IVW method, MR-Egger method, and weighted median method (WME). We also performed Cochran’s Q test to assess heterogeneity and used MR-Egger regression and MR-PRESO method to examine pleiotropy. Additionally, we conducted a leave-one-out analysis to assess the robustness of our findings.

Smoking is more prevalent among males and has been implicated in the etiology of IPF. Hence, we incorporated smoking as a covariate in our multivariate MR (MVMR) analysis.

To assess the causal relationship between IPF and testosterone, estradiol, and estrogen sulfotransferase, we conducted reverse MR analyses employing consistent methods and settings.

Data sources

In this study, genetic data for testosterone, estradiol, estrogen sulfotransferase, and IPF were obtained from the IEU GWAS database (https://gwas.mrcieu.ac.uk/). All data used in this study are in the public domain and do not require additional ethical approval. Study populations were of European ancestry to minimize potential bias due to racial factors. The dataset for testosterone (GWAS ID: ebi-a-GCST90014013) included 353,805 samples and 10,783,644 single nucleotide polymorphisms (SNPs). The dataset for estradiol (GWAS ID: ebi-a-GCST90020092) consisted of 206,927 samples and 16,136,413 SNPs. The dataset for estrogen sulfotransferase (GWAS ID: prot-a-2892) included 3,301 samples and 10,534,735 SNPs. The dataset for IPF (GWAS ID: finn-b-IPF) comprised 198,014 samples and 16,380,413 SNPs. The dataset for ever smoked (GWAS ID: ukb-a-236) comprised 336,067 samples and 10,894,596 SNPs. (Table 1).

Table 1 Information of the exposures and outcome datasets
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Instrumental variables

IVs are genetic variants associated with the exposure of interest. In this study, the exposure factors are testosterone, estradiol, and estrogen sulfotransferase, with IPF serving as the outcome. To ensure a strong correlation between genetic variation and exposure, we extracted IVs for testosterone, estrogen sulfotransferase with a threshold of P < 5 × 10− 8 and for estradiol with a threshold of P < 5 × 10− 7 (only 2 SNPs were obtained with P < 5 × 10− 8 for estradiol). Furthermore, to mitigate linkage disequilibrium (LD), we set clustering thresholds at r2 < 0.001 and a minimum intergenic distance of > 10,000 kb. We then excluded SNPs with an F-statistic less than 10, calculated using the formula F = R2(n-k-1)/k(1-R2), to avoid weak IVs. Additionally, we ensured data harmonization by removing palindromic SNPs. Subsequently, we employed LDlink (https://ldlink.nci.nih.gov/) to manually curate and eliminate SNPs associated with confounding factors and outcomes. Risk factors linked to IPF encompass occupational exposures (Work-related exposures to inhaled dust, asbestos, metal and/or wood dust), air pollution, gastro-oesophageal reflux disease, obstructive sleep apnoea, and viral infections [26]. Lastly, we performed a global outlier test using MR-PRESO and removed any outliers.

MR analysis

In this study, all statistical analyses were performed utilizing the “TwoSampleMR”,“MR-PRESSO”, and “MVMR” packages and within the R statistical software, version 4.3.2. Causal effects were assessed using the IVW method, MR-Egger method, and WME method. The IVW method estimates the final causal effect by calculating the weighted average of the effect sizes and standard errors of each genetic variant, thereby reducing the impact of genetic variants with larger measurement errors [27]. The MR-Egger method accounts for the presence of an intercept and can be used to assess pleiotropy [28]. The WME method assumes that over half of the IVs are valid, weights each instrumental variable’s effect by its precision, and then calculates the median [29]. IVW is a robust method that fully utilizes all IVs and offers higher statistical power compared to other methods. Therefore, in this study, we adopted IVW as the primary method for evaluating causal effects, with the other methods used for result validation.

Sensitivity analysis

We conducted Cochran’s Q test to assess heterogeneity, used MR-Egger regression and MR-PRESO method to examine pleiotropy, and performed a leave-one-out analysis to assess robustness. A Cochran Q test with P > 0.05 indicates no heterogeneity. If the MR Egger intercept has a P > 0.05, it suggests no horizontal pleiotropy. If the MR-PRESO Global test has P < 0.05, it indicates the presence of horizontal pleiotropy. MR-PRESO also detects outlier SNPs, which we removed before re-conducting MR analysis. The leave-one-out analysis involves systematically removing each SNP and computing the remaining results to assess the impact of the excluded SNP on causal effects.

Results

Obtained instrumental variables

In total, 70 SNPs were employed as IVs for testosterone, while 6 SNPs were utilized for estradiol, and 3 SNPs were selected for estrogen sulfotransferase, all in accordance with the predefined criteria for IVs selection. In the reverse MR analysis, 6 SNPs were utilized as IVs for IPF. Comprehensive details regarding these selected IVs are presented in Supplementary Table S1-6.

MR results and sensitivity analysis for testosterone, estradiol, estrogen sulfotransferase and IPF

Genetically predicted serum testosterone levels were associated with a 58.7% reduced risk of IPF for everyone standard deviation increase (OR = 0.413, PIVW=0.029, 95% CI = 0.187 ∼ 0.912), while genetically predicted estrogen sulfotransferase levels were associated with a 32.4% increased risk of IPF for everyone standard deviation increase (OR = 1.324, PIVW=0.006, 95% CI = 1.083 ∼ 1.618). Leave-one-out analysis for estradiol revealed that rs2345568 had a significant impact on the results and was removed. No causal relationship was found between estradiol and IPF (OR = 1.094, PIVW=0.735, 95% CI = 0.650 ∼ 1.841).

Cochran’s Q test for IVW on testosterone, estradiol, and estrogen sulfotransferase had P-values of 0.24, 0.88, and 0.646, respectively, all greater than 0.05, indicating no significant heterogeneity. MR-Egger intercepts were 0.178, 0.83, and 0.87 for testosterone, estradiol, and MR-PRESO Global test P-values were 0.262 and 0.871 for testosterone and estradiol, respectively, all greater than 0.05. MR-Egger and MR-PRESO methods suggested no evidence of potential horizontal pleiotropy. The Fig. 2 shows the results. Leave-one-out analysis showed no statistically significant differences in the effect estimates for each SNP (Fig. 3). The scatter plots depict the estimated impact of IVs on exposure and outcomes (Supplementary Fig. 1). Forest plots, Funnel plots and Density plots can be found in supplementary Figs. 2–4.

Fig. 1
figure 1

Three assumptions for IVs in MR analysis

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Fig. 2
figure 2

Forest plot showing results and sensibility analysis from MR study

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Fig. 3
figure 3

The results of leave-one-out analysis for Testosterone, Estradiol, Estrogen Sulfotransferase and IPF in turn

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MVMR analysis adjusting for smoking

The MVMR results indicate that the associations of testosterone (OR = 0.442, P = 0.037, 95% CI = 0.205 ∼ 0.953) and estrogen sulfotransferase (OR = 1.314, P = 0.001, 95% CI = 1.118 ∼ 1.545) with the risk of IPF retained statistical significance after adjusting for smoking (Supplementary Table S7).

MR results and sensitivity analysis for IPF in relation to testosterone, estradiol, and estrogen sulfotransferase

No causal relationships were observed between IPF and testosterone (OR = 1.001, PIVW=0.51, 95% CI = 0.998 ∼ 1.004), estradiol (OR = 1.001, PIVW=0.958, 95% CI = 0.982 ∼ 1.019), or estrogen sulfotransferase (OR = 0.975, PIVW=0.251, 95% CI = 0.933 ∼ 1.018).

Cochran’s Q test for IVW on IPF with estradiol and estrogen sulfotransferase had P-values of 0.53 and 0.29, respectively, both greater than 0.05, indicating no significant heterogeneity. However, for IPF and testosterone, the IVW method had a Cochran’s Q test P-value of 0.04, suggesting the presence of heterogeneity. MR-Egger intercepts for IPF and testosterone, estradiol, and estrogen sulfotransferase were 0.78, 0.88, and 0.9, respectively, all greater than 0.05. MR-PRESO Global test P-values for IPF and testosterone, estradiol, and estrogen sulfotransferase were 0.169, 0.673, and 0.419, respectively. MR-Egger and MR-PRESO methods indicated no evidence of potential horizontal pleiotropy. The Fig. 4 shows the results. Leave-one-out analysis showed no statistically significant differences in the effect estimates for each SNP (Fig. 5). The scatter plots depict the estimated impact of IVs on exposure and outcomes (Supplementary Fig. 5). Forest plots, Funnel plots and Density plots can be found in supplementary Figs. 6–8.

Fig. 4
figure 4

Forest plot showing results and sensibility analysis from reverse MR study

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Fig. 5
figure 5

The results of leave-one-out analysis for IPF in relation to Testosterone, Estradiol, and Estrogen Sulfotransferase in turn

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Discussion

Our study employed a two-sample bidirectional MR approach to investigate the associations between testosterone, estradiol, estrogen sulfotransferase levels, and the risk of IPF. We observed that higher serum testosterone levels were associated with a decreased risk of IPF, while an increase in serum estrogen sulfotransferase levels may potentially elevate the risk of IPF. However, no causal relationship was found between estradiol levels and the occurrence of IPF. Further MVMR analysis confirms that the influence of testosterone and estrogen sulfotransferase on the risk of IPF persists even when accounting for smoking. In the reverse MR analysis, we did not find any causal relationships between IPF and testosterone, estradiol, or estrogen sulfotransferase.

Prior studies have suggested a potential role for sex hormones in the development of IPF, but findings have been inconsistent, and the exact mechanisms are still debated. Our MR results contribute new evidence to this ongoing debate. Our findings may shed light on the protective role of testosterone against IPF. Previous studies have reported significantly reduced testosterone levels in IPF patients, with a positive correlation between testosterone levels and telomere length, a common susceptibility factor in sporadic and familial IPF [17, 30]. Liu M et al. discovered a negative correlation between telomere length and the progression of IPF [31], suggesting that the regulation of telomere length may be one of the mechanisms by which testosterone influences IPF. TGF-β plays a crucial role in IPF pathogenesis by stimulating fibroblast activation and proliferation and is one of the targets of the anti-fibrotic drug Pirfenidone [32, 33]. Zhang G et al. demonstrated that testosterone propionate (an exogenous androgen) could improve renal fibrosis in aged rats by inhibiting the TGF-β1/Smad pathway and activating the nuclear factor erythroid 2-related factor 2/antioxidant response element(Nrf2-ARE) signaling pathway [16]. The renin-angiotensin system (RAS) is also involved in the pathogenesis of IPF, with angiotensin-converting enzyme - Angiotensin II - angiotensin type 1 receptor (ACE-AngII-AT1R) promoting tissue fibrosis and angiotensin-converting enzyme 2 - Angiotensin (1–7) - angiotensin type 2 receptor (ACE2-Ang(1–7)-AT2R) antagonizing fibrosis progression [34]. Despite increased AT2R expression in IPF patients, the AT1R pro-fibrotic axis still predominates. Yang X et al. found that testosterone could inhibit Ang II-induced excessive proliferation and collagen synthesis in cardiac fibroblasts by suppressing the extracellular signal-regulated kinase 1 and 2 (ERK1/2) pathway [15]. From these studies, we can infer that the protective role of testosterone in IPF may be associated with the inhibition of the TGF-β and Ang II pathways. Testosterone also possesses immunomodulatory properties, suppressing inflammation by increasing anti-inflammatory cytokine IL-10 and reducing pro-inflammatory cytokines tumor necrosis factor-alpha(TNFα), interleukin-1 beta(IL-1β), and interleukin-6(IL-6) [35]. IL-6 not only participates in IPF-associated inflammatory responses but also promotes fibroblast proliferation [36]. Furthermore, studies have shown that testosterone can improve mitochondrial function in heart, muscle, and brain tissues [37,38,39], while mitochondrial dysfunction plays a significant role in IPF pathogenesis [40].

It is noteworthy that IPF predominantly affects males, which seems to contradict the protective role of testosterone against IPF. Several potential explanations for this discrepancy deserve further consideration. Firstly, IPF is more commonly observed in middle-aged and elderly males, a demographic trend that may correlate with the known decline in testosterone levels with increasing age. Secondly, environmental factors such as occupational dust exposure and smoking, which are more prevalent in males, might counteract the protective effects of testosterone.

Mendoza-Milla C et al. found that dehydroepiandrosterone could exert anti-fibrotic effects by affecting fibroblast migration, proliferation, differentiation, and collagen synthesis [41]. Previous Mendelian randomization studies have indicated that hypothyroidism promotes the development of IPF, possibly due to enhanced oxidative stress and impaired mitochondrial function in a hypothyroid state [42, 43]. We speculate that estrogen sulfotransferase sulfonates dehydroepiandrosterone and thyroid hormones, rendering them inactive, may be one of the reasons estrogen sulfotransferase promotes IPF development.

Future studies should deeply investigate the molecular underpinnings of how sex hormones, especially testosterone and estrogen sulfotransferase, interact with the pathophysiological processes of IPF. This encompasses exploring their effects on fibroblast activity and the regulation of immune responses. Clinical trials are essential for evaluating the potential of sex hormone modulation as a therapeutic approach for IPF. Moreover, longitudinal research across various populations should be undertaken to elucidate the prognostic implications of sex hormone levels. Examining sex-specific differences may uncover distinct risk factors and therapeutic targets for each gender. These research pathways are designed to strengthen our understanding of the complex relationship between sex hormones and IPF, which could lead to innovative preventive and therapeutic perspectives for the condition.

This study is the first to utilize the MR method to assess the causal relationships between testosterone, estrogen, and estrogen sulfotransferase levels and the risk of IPF. Our MR analysis was based on large-sample GWAS data from European populations, providing sufficient statistical power for accurate estimation of causal effects. Additionally, our study effectively mitigated the potential for reverse causality and confounding factors.

Limitations

There are some limitations to our study. Firstly, since the GWAS data used in our study were derived from European populations, the generalizability of our findings to other populations may be limited. Therefore, future research should include more diverse populations to validate and extend these findings. Secondly, due to constraints in the original data, our study did not perform detailed stratified analyses by gender and age. Future studies should consider these key demographic variables for a more comprehensive understanding of their impact on genetic risk for IPF.

Conclusions

Our study suggests that genetically predicted higher serum testosterone levels may be associated with a reduced risk of IPF, while an increase in serum estrogen sulfotransferase levels may potentially elevate the risk of IPF. No causal relationship was found between estradiol levels and the risk of IPF. Furthermore, we did not identify any causal relationships between IPF and testosterone, estradiol, or estrogen sulfotransferase.

Data availability

All GWAS data used in this study are available in the IEU Open GWAS Project (https://gwas.mrcieu.ac.uk/).

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Acknowledgements

We express our gratitude to the IEU Open GWAS database for providing publicly available summary-level GWAS data for our study.

Funding

This study was supported by the Scientific Research Innovation Special Project from Putian University (2019SZP02). This funding body had no influence on the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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Authors and Affiliations

  1. The School of Clinical Medicine, Fujian Medical University, Fuzhou, China

    Qingying Xu, Guangwang Hu, Qunying Lin, Menghang Wu, Kenan Tang, Yuyu Zhang & Feng Chen

  2. Department of Respiratory Medicine, Putian Pulmonary Hospital, Putian, China

    Qunying Lin

  3. Department of Respiratory Medicine, Affiliated Hospital of Putian University, Putian, China

    Qunying Lin

Authors
  1. Qingying Xu
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  2. Guangwang Hu
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  3. Qunying Lin
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  4. Menghang Wu
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  5. Kenan Tang
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  6. Yuyu Zhang
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  7. Feng Chen
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Contributions

QX and QL conceived and designed the study. QX, GH, MW, KT, YZ, FC conducted data analysis. QX wrote the manuscript and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Qunying Lin.

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Xu, Q., Hu, G., Lin, Q. et al. The association between testosterone, estradiol, estrogen sulfotransferase and idiopathic pulmonary fibrosis: a bidirectional mendelian randomization study. BMC Pulm Med 24, 435 (2024). https://doi.org/10.1186/s12890-024-03198-0

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Keywords

BMC Pulmonary Medicine

ISSN: 1471-2466

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