Causal Relationship between Gut Microbiota and Pulmonary Embolism: An Analysis Using Mendelian Randomization
Categoria dell'articolo: Original Paper
Pubblicato online: 18 giu 2025
Pagine: 153 - 164
Ricevuto: 16 dic 2024
Accettato: 09 apr 2025
DOI: https://doi.org/10.33073/pjm-2025-013
Parole chiave
© 2025 LILAN CEN et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Venous thromboembolism (VTE) encompasses pulmonary embolism (PE) and deep vein thrombosis. A sudden onset characterizes PE and carries the potential for fatality, with limited options for early detection and management of changeable risk factors. The pathogenesis of PE is multifaceted, involving a mix of environmental and genetic risk factors, with inflammation having a significant impact on the advancement of this condition (Lutsey and Zakai 2023). Inflammation serves to activate endothelial cells, platelets, and white blood cells, thereby initiating clotting processes and contributing to the development of coagulation disorders as well as increased pro-inflammatory cytokine levels, chemokines, and diverse white cell subtypes (Saghazadeh and Rezaei 2016). The gut microbiome (GM) is connected to the etiology of numerous inflammatory disorders, with intestinal dysbiosis being linked to an increased prevalence of venous thromboembolism (Kappelman et al. 2011; Freuer et al. 2022). The dysregulation of GM can induce the involvement of innate immune cells, platelets, and vascular endothelial cells in inflammatory pathways, which release multiple clotting proteins and promote a pro-thrombotic state (Lutsey and Zakai 2023). Concurrently, recent research has extensively investigated the “gut-lung axis” relationship, revealing additional connections between intestinal flora metabolites and alterations in pulmonary function. Data indicates that the composition of the gut microbiome influences the pathogenesis of long-term pulmonary obstruction (Hasan et al. 2020) and asthma (Barcik et al. 2020) through its regulatory impact on inflammation. While there is a known correlation between intestinal dysbiosis and a heightened risk of VTE, the specific molecular pathways through which gut microbiota contribute to the development of VTE, particularly PE, have not yet been thoroughly investigated.
After acute myocardial infarction and stroke, VTE, which includes PE and deep vein thrombosis, is the third most common vascular disease, with an estimated 10 million cases annually, posing a significant global health challenge (Raskob et al. 2014). PE, a frequently encountered and potentially life-threatening condition in the emergency department, typically results in mortality within a short timeframe post-diagnosis. PE can lead to a range of pathophysiological disorders, with clinical thrombosis resulting from of vascular wall damage, alterations in blood flow, and abnormalities in blood components (Ballard et al. 2012). The development of PE is intricate and is impacted by a confluence of environmental and genetic variables. Increasing data indicates that inflammation contributes significantly to the risk of developing PE (Zhang et al. 2023). Inflammation not only triggers the coagulation process, but also contributes to coagulation dysfunction and an elevation in pro-inflammatory cytokines, chemokines, and different types of white blood cells. Activated white blood cells are the primary origin of tissue factor positive procoagulant microparticles, which have the potential to induce thrombus formation and growth (Zhang et al. 2023). Despite significant progress in identifying and treating lung embolism, further research is warranted to identify modifiable risk factors in a timely manner for effective prevention and treatment. The GM is known to perform a significant role in the pathogenesis of obesity, sepsis/infection, inflammatory bowel disease, and intestinal failure and has been associated with a higher risk of VTE (Miehsler et al. 2004; Ley et al. 2006; Kaplan et al. 2015; Gonzalez-Hernandez et al. 2016). Disruption of the GM by environmental or genetic influences can trigger inflammatory pathways in innate immune cells, platelets, and vascular endothelial cells, which causes coagulation protein to be released and promotes an inflammatory response, leading to a prothrombotic state (Zhu et al. 2016; Jäckel et al. 2017). Research has demonstrated that dysregulation of the GM can result in cellular dysfunction and tissue damage, which are collectively referred to as lesions in multiple organs, including the lungs, a phenomenon known as the gastrointestinal-lung axis (Budden et al. 2017). The gastrointestinal-lung axis is a bidirectional communication system between the gut and the lungs, which is mainly mediated by the immune, nervous, and circulatory systems. In the gut, the normal gut microbiota plays a crucial role in maintaining intestinal homeostasis. When the gut microbiota is dysregulated, such as antibiotic use, diet changes, or infections, it can lead to increased intestinal permeability. This allows endotoxins, such as lipopolysaccharides, and microbial metabolites to translocate from the gut into the bloodstream. Once in the circulation, these substances can reach the lungs via the systemic circulation. In the lungs, they may trigger an inflammatory response, affecting pulmonary function and potentially contributing to the development of lung diseases. Additionally, gut microbiota changes can activate the immune cells in the gut-associated lymphoid tissue. These activated immune cells can then circulate to the lungs through the bloodstream and lymphatic system, modulating the local immune response. Conversely, lung inflammation can also impact the gut microbiota. For instance, cytokines and other inflammatory mediators produced in the lungs during a respiratory infection can reach the gut through circulation, altering the composition and function of the gut microbiota. As such, this axis helps hormones, cytokines, endotoxins, and microbial metabolites enter the bloodstream (Dang and Marsland 2019). These results offer insight into the association between gut microbiota and thromboembolism, suggesting a potential link to PE. Nevertheless, it is unclear how gut microbiota contributes to PE pathogenesis, and this mechanism remains incompletely understood.
The Mendelian randomization (MR) approach utilizes integrated genome-wide association studies (GWAS) data to identify suitable single nucleotide polymorphisms (SNPs) serving as useful variables (IV) in evaluating the causal association among an exposure combined with a result (Birney 2022). MR employs random allocation in allelic inheritance, mitigates the impact of confounding variables, and does not alter the genetic sequence of individuals, facilitating the investigation of the cause-and-effect link between GM and PE via MR research. MR methods have been utilized to evaluate potential causal associations between the gut microbiota (GMS) and lung conditions such as chronic obstructive pulmonary disease, asthma, and thromboembolism (Hasan et al. 2020; Freuer et al. 2022; Wei et al. 2023). However, while several recent studies have explored the relationship between gut microbiota and venous thromboembolism (Wang et al. 2023; Meng et al. 2024; Xi et al. 2024), the specific causal relationship between gut microbiota and PE using MR analysis warrants further investigation.
This research chose GM as the independent variable and PE as the dependent variable in a Mendelian randomization analysis. The study assessed the possible reason for the association between GM and PE through the lens of host genetics, offering a foundational framework for future investigations into the intricate mechanisms underlying PE. Furthermore, the identification of specific GM profiles in PE patients may lead to the finding of new biomarkers as well as the growth of improved diagnostic and therapeutic approaches.
Two-sample Mendelian randomization examined the causal relationship between GM and PE. To mitigate the influence of confounding variables on the findings, the Mendelian randomization analysis followed three primary presumptions: i) IVs were exclusively linked to the exposure variables; ii) the selected IVs were not correlated with potential confounders (GM taxa and PE); iii) IVs could solely impact PE through GM taxa. Fig. 1 illustrates the fundamental principles underlying the relationship between GM and PE.

Illustrates the principles of Mendelian randomization (MR) analysis and its three fundamental assumptions. The diagram was generated using Figdraw2.0 software, with the unique identifier RRSAAba96a.
We conducted a filtering process for SNPs, which were determined by earlier screening for SNP threshold. To guarantee more thorough results, SNPs with a threshold of
The PE outcome data was taken from the Open GWAS database at IEU (
This study primarily utilizes the inverse variance weighting (IVW) technique as the main analytical method to evaluate the association between GM and PE, with the additional use of weighted Mode, Simple Mode, Weighted Median (WM), and MR-Egger as the four additional methods. Cochran’s Q statistic was used to evaluate the heterogeneity of IVs; a
R software v4.3.1 (R Core Team 2023) was used for data visualization and statistical analysis. “TwoSampleMR” packages for R and “MR-PRESSO” were utilized for GM and PE’s causal relationship examined using Mendelian randomization analysis. Evidence of a possible causal relationship was assessed at a significance level of
1,531 SNPs in all that are linked to PE were found across 211 bacterial groups using an LD test, MR-PRESSO test,
The IVW method was utilized to ascertain four GMs that exhibited robust causal associations with PE, as evidenced in Table I.
MR results of causal links between gut microbiota and pulmonary embolism risk.
Classification | SNP | SE | OR (95%Cl) | Pleiotropy | Heterogeneity | MR-PRESSO | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
Egger intercept | SE | Method | Q | ||||||||
9 | 0.0007 | 0.031 | 0.998 (0.997–1.000) | 0.0003 | 0.0003 | 0.424 | MR-Egger | 5.228 | 0.632 | 0.630 | |
IVW | 5.948 | 0.653 | |||||||||
9 | 0.0006 | 0.038 | 0.998 (0.996–1.000) | –7.75 × 10−5 | 0.0004 | 0.851 | MR-Egger | 7.609 | 0.368 | 0.494 | |
IVW | 7.650 | 0.468 | |||||||||
11 | 0.0012 | 0.032 | 0.997 (0.995–1.000) | –0.0003 | 0.0004 | 0.537 | MR-Egger | 10.079 | 0.344 | 0.403 | |
IVW | 10.541 | 0.394 | |||||||||
9 | 0.0009 | 0.049 | 0.998 (0.996–1.000) | –0.0001 | 0.0002 | 0.634 | MR-Egger | 4.684 | 0.698 | 0.794 | |
IVW | 4.931 | 0.765 |
SNP – single nucleotide polymorphism; SE – standard error; OR – odds ratio; Q – Cochran’s Q; MR-PRESSO – Mendelian randomization pleiotropy residual sum and outlier
We found that four gut microbiota (GMS) were linked to a lower chance of PE (Fig. 2):

The forest plot illustrates the causal relationships between four GM (

The scatter plots were used to examine the correlation between four GM and the likelihood of developing PE disease: A)
In order to mitigate potential bias, various actions were implemented to assess the MR’s sensitivity analyses and identify any possible pleiotropy of instrumental variables in each phenotype in turn. According to Cochrane’s Q test (

The leave-one-out sensitivity analysis demonstrated that the exclusion of any single SNP did not significantly impact the outcomes.

The funnel plot analysis indicated the absence of heterogeneity in the experiments as confirmed by the IVW and MR-Egger tests.
Recently, several MR studies (Wang et al. 2023; Meng et al. 2024; Xi et al. 2024) have indeed investigated the relationship between gut microbiota and VTE. Similar to these studies, our research also found that
This research investigated the potential causal link between GM and PE through a genetic perspective utilizing MR techniques. The study employed independent GM-related SNPs identified in GWAS as instrumental variables and evaluated their impact on PE risk using MR methodologies. Following the implementation of the IVW technique as the principal causal analysis, the results indicated that four specific GM taxa -
Our findings align with some recent studies that have explored the relationship between gut microbiota and pulmonary diseases. For example, similar to our results on
Regarding new clinical findings, while previous studies mainly focused on the overall relationship between gut microbiota and VTE, our study specifically identified four gut microbiota genera with potential protective effects against PE. This provides more targeted information for future clinical research. For example, it may guide the development of personalized probiotic therapies. Supplementing specific bacteria such as
This study represents the initial Mendelian randomized investigation into the causal involvement of GM in PE. Employing MR Analysis, we examined the GM taxa and possible causal relationships PE through the lens of host genetics, confirming its impact on altering susceptibility to PE. The composition of the gut microbiome is known to change during disease progression, and in the case of pulmonary embolism, it likely undergoes multiple changes as the disease develops through its earlier stages. The protective bacteria identified in our study, such as
The bacterial genera
The research presents several strengths alongside certain constraints. These strengths include the novel utilization of two samples for MR analysis, allowing for an analysis of potential resonal relationships between GM and PE at the genus level. Additionally, as compared to previous randomized controlled studies, the gut microbiota data we used is the GWAS to date, giving the study a larger sample size. Lastly, the significant epidemiological implications of MR analysis suggest its ongoing relevance and potential expansion later on. It is important to recognize this study’s limitations. Besides the issues we have already mentioned, other potential confounding factors could influence the results. For example, diet is closely related to the composition of gut microbiota. Different dietary patterns, such as high-fiber or high-fat diets, may affect the abundance and function of the gut microbiota, and at the same time, diet can also impact the body’s inflammatory state and coagulation function, which are relevant to the development of PE. Lifestyle factors like exercise and smoking also cannot be ignored. Regular exercise may modulate the gut-lung axis through various mechanisms, and smoking can disrupt the balance of the gut microbiota and increase the risk of inflammation and thrombosis. However, due to the nature of our data source, these factors were not accounted for in the current analysis. In addition, it is important to recognize this study’s limitations, including the following: i) While our study supports the MR hypothesis, it does not definitively eliminate the potential for weak instrument bias. ii) Incorporating individuals of European descent in the GWAS data may limit the study’s findings’ applicability to other ethnic populations. iii) The exposure data only classified genus, restricting the ability to analyze relationships at the species level. Insufficient IV availability for reverse MR analysis precludes the determination of the possible link of causation between GM and PE. To address the concern about the generalizability of our findings, we acquired GWAS data of PE from
While bacteria are the major component of the gut microbiome, other components such as the mycobiome, viruses, archaea, and protists can also significantly modulate circulatory and tissue dysfunction. For example, certain fungi in the gut mycobiome may interact with the immune system and influence inflammation, which is closely related to the development of PE. Viruses in the gut virome can affect the gut epithelial barrier function, potentially leading to changes in the translocation of microbial products and subsequent effects on the host’s health. Archaea may contribute to the metabolism of the gut microbiota, and protists can interact with bacteria and the host immune system in complex ways. However, in the present study, we mainly focused on bacteria and did not fully consider the impact of these other microbial components. This is a limitation of our study. Future research should aim to comprehensively investigate the relationships between all components of the gut microbiome and PE to gain a more complete understanding of the underlying mechanisms.
Hence, this finding represents a preliminary investigation at the species level. Subsequent research endeavors intend to broaden the sample size and investigate the correlation between GM taxa and PE at the species level to offer enhanced theoretical backing for investigating the “gut-lung” axis mechanism.
Our study employs a Mendelian randomization analysis with two samples using publicly available GWAS aggregate research to establish the causal relationship among GM (specifically
These findings have important implications for future research and clinical practice. Regarding potential therapeutic interventions, we could consider developing probiotic-based therapies. For example, supplementing with
On the clinical side, the identified associations could be used to develop new risk prediction models for PE. By incorporating information about an individual’s gut microbiota composition, we can more accurately assess their risk of developing PE, especially in high-risk populations. This could enable earlier preventive measures, such as targeted anticoagulant therapy or lifestyle modifications.
Furthermore, these discoveries could offer a theoretical framework for advancing innovative interventions and therapies for PE targeted at enhancing or altering GM.