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Causal relationship between immune cells and venous thromboembolism: a bidirectional two-sample Mendelian randomization study

Thrombosis Journal volume 23, Article number: 78 (2025) Cite this article

Abstract

Background

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Venous thromboembolism (VTE), which includes Pulmonary embolism (PE) and Deep vein thrombosis (DVT), is a complex vascular disorder with poorly understood pathological mechanisms. Emerging research highlights the potential involvement of immune cells in the pathogenesis of VTE, although their causal relationship remains unproven.

Methods

To systematically assess the causal relationships between 731 immune phenotypic traits and VTE, PE, and DVT, this study employed a bidirectional, two-sample Mendelian randomization (MR) approach. In the forward MR analysis, immune cell characteristics were treated as the exposure, while VTE, DVT, and PE were the outcomes. In the reverse MR analysis, VTE, DVT, and PE were considered exposures, with immune cell characteristics as the outcomes. To ensure the robustness, heterogeneity, and control for potential confounding factors in the study results, we performed a sensitivity analysis. Furthermore, we applied the False discovery rate (FDR) method to account for statistical bias arising from multiple comparisons.

Results

After FDR correction, we identified potential causal associations between four immune cell types and VTE, six types and PE, and three types and DVT.

Conclusion

This study demonstrates that specific immune cell types are causally linked to VTE, DVT, and PE, providing valuable insights for future clinical research.

Introduction

Venous thromboembolism (VTE), a common global health issue encompassing Deep vein thrombosis (DVT) and Pulmonary embolism (PE), demonstrates significant morbidity and mortality rates [1]. VTE ranks as the third leading cause of death related to cardiovascular diseases worldwide, preceded only by coronary artery disease and ischemic stroke [2]. The 2021 report from the American Heart Association estimated that approximately 1,220,000 cases of VTE occur annually in the United States [3]. Furthermore, research data indicate that six European countries report approximately 466,000 cases of DVT, 296,000 cases of PE, and 370,000 deaths attributable to VTE annually, underscoring the substantial public health burden [4].

The immune system consists of various immune cells, cytokines, and markers that regulate immune responses and inflammation [5]. The relationship between immune cells and thrombus formation is complex and multifaceted, research demonstrates that the immune system play a crucial role in thrombus formation and resolution, engaging in inflammatory responses and directly participating in maintaining the balance between procoagulation and anticoagulation processes [1, 6]. Growing evidence suggests that chronic inflammation plays a pivotal role in the progression of thrombus formation [7]. In the pathogenesis of venous thrombus formation, circulating cytokines contribute to a hypercoagulable state, endothelial dysfunction, and alterations in hemodynamics [8]. These cytokines play a pivotal role in regulating the inflammatory response, and studies have shown that genetically predicted elevated PE risk is causally linked to lymphocyte subsets [9]. Inflammatory biomarkers demonstrate variable levels across various stages of VTE, and may serve as potential risk factors for subsequent VTE events [10]. Specific immune cells may indicate the onset of VTE. Identifying additional factors associated with VTE pathogenesis, especially biomarkers, could enhance disease prevention, optimize clinical management, and advance the development of therapeutic agents for VTE [11]. Current observational studies may be subject to bias due to potential confounding factors and reverse causality, and there is ongoing debate regarding the relationship between immune cell phenotypes and thrombosis. Genome-wide association studies (GWAS) analyze genetic variations, loci, and pathways, playing a crucial role in identifying the intrinsic genetic factors of diseases [12]. This approach will also contribute to exploring the link between immune inflammation and genetic background in patients with venous thromboembolism.

Mendelian randomization (MR) is an epidemiological method that employs genetic variations as instrumental variables to infer causal relationships between exposures and outcomes, grounded in Mendelian genetic principles [13]. It utilizes genetic variants to establish causal relationships between exposures and outcomes. Compared to other statistical methods, MR can reduce biases caused by confounding and reverse causation [14]. In this study, a bidirectional, two-sample MR analysis was performed to systematically assess the causal relationship between immune cell phenotypes and VTE, including DVT and PE.

Materials and methods

Study design

This study employs bidirectional two-sample MR to assess the causal relationship between 731 immune cell phenotypes and the risk of VTE, including PE and DVT. MR relies on three fundamental assumptions: (1) Instrumental variables (IVs) are strongly associated with the exposure, (2) IVs are independent of any confounding factors, and (3) IVs affect the outcome solely through their influence on the exposure [15, 16]. The study design is depicted in Fig. 1. All datasets used in this study are publicly available and do not require additional ethical approval.

Fig. 1
figure 1

Study Design. Abbreviations: IVs, instrumental variables; SNPs, single nucleotide polymorphisms; GWAS, genome-wide association study; AC, absolute cells; MFI, median fluorescence intensity; MP, morphological parameters; RC, relative cells

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Data sources

The GWAS data for 731 immune cell phenotypes (ranging from GCST90001391 to GCST90002121) were obtained from the GWAS Catalog database (https://gwas.mrcieu.ac.uk/) [17]. The GWAS Catalog is a publicly accessible database that consolidates data from GWAS studies exploring associations between SNPs and diseases or other physiological traits. This database includes data from 3,757 adults of European Sardinian descent, 57% of whom are female. Following adjustments for sex and age, 22 million SNP sites were retained for association analysis [18]. The GWAS datasets for VTE, PE, and DVT were obtained from the Finnish Biobank database (https://finngen.gitbook.io/documentation/v/r10). The VTE study involved 248,674 Europeans (138,776 women, 106,624 men)(Phenocode: I9_VTE ), with a median age of 60.38 years at the first occurrence of VTE (58.17 years for women, 62.92 years for men), including 412,181 total samples (Ncase = 21,021, Ncontrol = 391,160). The PE study involved 122,590 Europeans (66,761 women, 53,967 men)(Phenocode: I9_PULMEMB ), with a median age of 65.69 years at the first occurrence of PE (64.67 years for women, 66.76 years for men), including 411,174 samples (Ncase = 10,046, Ncontrol = 401,128). The DVT study involved 75,938 Europeans (40,582 women, 34,466 men)(Phenocode: I9_PHLETHROMBDVTLOW ), with a median age of 59.00 years at the first occurrence of DVT (57.33 years for women, 60.77 years for men), including 363,612 samples (Ncase = 6,501, Ncontrol = 357,111). The Finnish Biobank database provides comprehensive statistics, including genetic variants linked to thrombotic diseases, based on a large-scale European dataset, ensuring the robustness and reliability of the findings.

IVs selection

To ensure the validity of causal estimates, the selection of IVs is based on stringent criteria. The Single nucleotide polymorphisms (SNPs) screened must reach genome-wide significance levels (P < 1 × 10−5) [19]. To reduce bias caused by linkage disequilibrium, SNPs are filtered with an r²<0.1 threshold within a 500 kb window [20]. SNPs with an F-statistic greater than 10 are regarded as strong instruments to mitigate weak instrument bias.

Statistical analysis

Statistical analysis was performed using R software (version 4.3.3). To assess the causal relationship between 731 immune phenotypes and VTE, PE, and DVT, five MR methods were employed. The primary analysis utilized the Inverse variance weighted (IVW) method to integrate causal effects from multiple instrumental variables, with supplementary sensitivity analyses, including the weighted median method and MR-Egger regression [21]. In the reverse MR analysis, VTE, PE, and DVT were treated as exposure variables, while immune cell traits were considered as outcome variables. The SNP selection criteria were consistent with those in the forward analysis, with False discovery rate (FDR) correction applied to control for false discovery rates (P < 0.05). Heterogeneity was assessed using Cochran’s Q test, and horizontal pleiotropy was assessed through the MR-Egger intercept test. A leave-one-out analysis was conducted to examine the influence of each individual SNP on the overall causal estimates [22, 23].

Results

Selection of IVs

Following preliminary screening, potential causal relationships were identified between five types of immune cells and VTE, six with PE, and three with DVT. All IVs displayed F-statistics greater than 10.

Causal effect of immune cells on VTE

After FDR correction (PFDR < 0.05), we identified five immune cell types potentially associated with a causal relationship to VTE. CD62L- DC AC exhibited a positive correlation with VTE. In contrast, DN (CD4-CD8-) NKT% lymphocytes, CD16 on CD14- CD16 + monocyte, CD64 on CD14 + CD16- monocyte, and SSC-A on HLA DR + NK cells were negatively correlated with VTE.

The results from IVW analysis are as follows: DN (CD4-CD8-) NKT %lymphocyte (P = 0.0005; OR 95% CI = 0.962 [0.942–0.983], PFDR = 0.0462), CD62L- DC AC (P = 0.0010; OR 95% CI = 1.030 [1.012–1.048], PFDR = 0.0462), CD16 on CD14- CD16 + monocyte (P = 0.0011; OR 95% CI = 0.985 [0.976–0.994], PFDR = 0.0462), CD64 on CD14 + CD16- monocyte (P = 0.0010; OR 95% CI = 0.981 [0.970–0.992], PFDR = 0.0462), and SSC-A on HLA DR + NK cells (P = 0.0007; OR 95% CI = 0.966 [0.946–0.985], PFDR = 0.0462). The results of other forward MR methods are provided in the supplementary material (1) In the reverse MR analysis examining the relationship between immune cells and VTE, a causal link was identified between VTE and DN (CD4-CD8-) NKT %lymphocyte, with the IVW result as follows: DN (CD4-CD8-) NKT %lymphocyte (P = 0.0013; OR 95% CI = 1.070 [1.027–1.115], PFDR = 0.0135). The results of other reverse analyses are provided in the supplementary material (2) To rigorously control for confounding factors and prevent interference from immune cells with established causal relationships, we excluded such immune cells from the reverse MR analysis of VTE. Ultimately, four immune cell types potentially associated with causal relationships to VTE were identified, as depicted in Fig. 2.

Fig. 2
figure 2

Forest plot of MR results for immune cells and VTE. Abbreviations: FDR, false discovery rate

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Causal effect of immune cells on PE

Our study identified six types of immune cells that potentially have a causal relationship with PE. CD86 + myeloid DC AC, CD86 + myeloid DC %DC, and CD20 on naive-mature B cells exhibited positive correlations with PE. Conversely, HLA DR + NK AC, HLA DR + NK %CD3- lymphocyte, and SSC-A on HLA DR + NK cells showed negative correlations with PE. The results from the IVW analysis are as follows: CD86 + myeloid DC AC (P = 0.0003; OR 95% CI = 1.041 [1.018–1.064], PFDR = 0.0413), CD86 + myeloid DC %DC (P = 0.0001; OR 95% CI = 1.044 [1.022–1.067], PFDR = 0.0319), CD20 on naive-mature B cells (P = 0.0005; OR 95% CI = 1.061 [1.026–1.098], PFDR = 0.0478), HLA DR + NK AC (P = 0.0002; OR 95% CI = 0.951 [0.926–0.976], PFDR = 0.0413), HLA DR + NK %CD3- lymphocytes (P = 0.0001; OR 95% CI = 0.953 [0.931–0.976], PFDR = 0.0319), and SSC-A on HLA DR + NK cells (P = 0.0003; OR 95% CI = 0.948 [0.921–0.976], PFDR = 0.0413). The results of other forward MR methods are provided in the supplementary material (1) In the reverse MR analysis, all IVW results were not significant (P > 0.05), indicating that PE does not have a significant effect on the immune cells studied. The results of other reverse analyses are provided in the supplementary material (2) The findings suggest that six immune cell types may have causal relationships with PE, as depicted in Fig. 3.

Fig. 3
figure 3

Forest plot of MR results for immune cells and PE. Abbreviations: FDR, false discovery rate

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Causal effect of immune cells on DVT

Our findings suggest that three types of immune cells may have causal relationships with DVT. These include IgD- CD38dim %B cell, CD45RA + CD8br AC, and CD4 on CD39 + CD4 + T cells, all of which are negatively correlated with DVT.

The results from IVW analysis are as follows: IgD- CD38dim %B cell (P = 0.0002; OR 95% CI = 0.898 [0.849–0.951], PFDR = 0.0304), CD45RA + CD8br AC (P = 0.0001; OR 95% CI = 0.874 [0.819–0.934], PFDR = 0.0182), and CD4 on CD39 + CD4 (P = 0.0001; OR 95% CI = 0.953 [0.930–0.976], PFDR = 0.0182). The results of other forward MR methods are provided in the supplementary material (1) In the reverse MR analysis, all IVW results were not significant (P > 0.05), indicating that DVT does not have a significant effect on the immune cells studied. The results of other reverse analyses are provided in the supplementary material (2) The final results confirm the potential causal relationships between these three types of immune cells and DVT, as depicted in Fig. 4.

Fig. 4
figure 4

Forest plot of MR results for immune cells and DVT. Abbreviations: FDR, false discovery rate

Full size image

Sensitivity analysis

In the sensitivity analysis, we evaluated heterogeneity and pleiotropy among the immune cell types studied and their associations with VTE, PE, and DVT. The analyses yielded P-values greater than 0.05, indicating the absence of heterogeneity and pleiotropic effects in the SNPs. Additionally, the stability of our findings was confirmed through leave-one-out analyses. The leave-one-out plot can be provided in supplementary material 3. The heterogeneity results are presented in Table 1 and the pleiotropy analysis results in Table 2.

Table 1 Heterogeneity of immune cells and venous thromboembolism
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Table 2 Pleiotropic tests of immune cells and venous thromboembolism
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Discussion

This study employed bidirectional two-sample MR analysis to explore the causal relationships between genetic predisposition in 731 immune cell phenotypes and the risk of VTE, including PE and DVT. By systematically assessing potential causal associations between various immune phenotypes and VTE risk using large public genetic datasets, we identified four immune cell types causally associated with VTE, six types with PE, and three types with DVT, according to rigorous inclusion criteria and sensitivity analyses.

Persistent inflammation driven by immune activation is a known risk factor for VTE [24]. Dendritic cells lacking CD62L may promote immune responses through their roles in pro-inflammatory environments, activating endothelial cells, upregulating coagulation factors, and increasing platelet aggregation, all of which are closely related to thrombosis formation [25, 26]. Therefore, CD62L-negative dendritic cells are considered a risk factor for VTE due to their role in sustaining a pro-inflammatory state. Studies suggest that CD62L is crucial for regulating leukocyte adhesion and migration, and its shedding or reduction may indicate the activation state of immune cells [27]. Activated CD62L- DCs may affect their function in secondary lymphoid organs, leading to decreased antigen-presenting capability, further triggering and maintaining a peripheral pro-inflammatory environment that promotes thrombosis formation [28]. CD86 functions as a critical co-stimulatory molecule in immune responses, particularly during antigen presentation between dendritic cells and T cells [29]. This molecule is constitutively expressed on various antigen-presenting cells, including myeloid dendritic cells, and engages CD28 on T cells to deliver essential activation signals [30]. This process is crucial in initiating immune responses, but in pathological states, it may lead to excessive immune activation [31]. In inflammatory milieus, hyperactivation of CD86 + myeloid dendritic cells may mediate endothelial injury, subsequently triggering platelet activation and aggregation. In a sustained pro-inflammatory state, high expression of CD86 could exacerbate vascular injury and coagulation, thereby affects blood flow to the lungs [32]. Studies on acute myeloid leukemia have shown that CD86 may induce excessive immune responses, causing endothelial damage and thrombus formation in chronic inflammatory states [33]. The expression of CD20 on B cells is regarded as a marker of their development and maturation, with high expression on initially mature B cells indicating their active state in humoral immunity [34]. By secreting antibodies and forming immune complexes, B cells may trigger the coagulation system, increasing the risk of thrombus formation and thus leading to PE [35]. Research investigating the impact of decreased CD20 expression on B cells following anti-CD20 antibody treatment has demonstrated that, in certain cases, their activation and influence on the immune system may contribute to enhanced thrombus formation [36].

We identified a negative causal relationship between NK cells and both VTE and PE. In immune responses, HLA-DR⁺ NK cells display phenotypic features of both NK cells and dendritic cells, thus playing a critical role. Upon stimulation, HLA-DR⁺ NK cells perform their functions by producing pro-inflammatory cytokines, undergoing degranulation, and proliferating. Additionally, they can uptake antigens and present them to T cells, thereby triggering T cell activation and proliferation, while also providing essential co-stimulatory signals for T cell differentiation [37]. Changes in NK cell function may affect the risk of thrombosis, suggesting that immune-targeted interventions might have potential clinical applications in thrombosis management [38]. However, some studies have demonstrated that, in addition to being present in the blood and tissues of healthy mice and humans, HLA-DR + NK cells are also observed in various pathological conditions associated with chronic inflammatory diseases, where their abundance in peripheral blood may be significantly increased [9]. In response to exogenous stimuli, HLA-DR expression on NK cells is upregulated [39]. Currently, no studies have examined the relationship between HLA-DR + NK cells and thrombosis. Future research should integrate both basic and clinical studies to clarify the underlying mechanisms, potentially leading to the development of new strategies for treating VTE.

The role of monocyte subgroups in VTE may be related to their immunoregulatory functions and control over inflammatory responses. Monocytes, an essential component of the innate immune system, participate in the formation of intravascular thrombi, i.e., immunothrombosis [40]. CD16 is expressed differently across various subtypes of monocytes [41]. CD16 + monocytes are recognized as a hyperinflammatory subset that exacerbates inflammatory responses through enhanced production of pro-inflammatory cytokines and chemokines [42]. Our study shows that an increase in CD16 + monocytes is associated with a reduced risk of VTE. The role of CD16 + monocytes depends on the different pathological stages of VTE; during the acute phase of VTE, CD16 + monocytes (especially non-classical and intermediate monocytes) may be involved in the formation and maintenance of thrombi, but during the recovery phase, as inflammation subsides and thrombi resolve, these cells may participate in thrombus clearance and tissue repair [43]. A study on chronic thromboembolic pulmonary hypertension utilized single-cell RNA sequencing technology to deeply explore the composition of immune cells, showing a significant increase in CD16 + monocytes in CTEPH patients, suggesting that these cells may play an important role in thrombus formation and the long-term remodeling process of pulmonary vessels [44]. The development of VTE often accompanies excessive activation of the inflammatory response; CD16 + monocytes may reduce the risk of thrombus formation by inhibiting the release of pro-inflammatory cytokines, helping to reduce endothelial damage, platelet aggregation, and excessive activation of coagulation factors [45, 46 ]. CD64 is a high-affinity Fc receptor predominantly expressed on monocytes and macrophages. It reduces endothelial cell activation and alleviates the pro-inflammatory state by promoting the binding and internalization of immune complexes, thereby lowering the risk of thrombosis [47]. Studies exploring the association between various inflammatory biomarkers, including CD64 expression on monocytes, and VTE risk have shown that inflammatory processes play a key role in thrombus formation [10].

B cells and T cells may have a negative correlation with DVT due to their immunoregulatory functions, possibly reducing DVT risk through the production of anti-inflammatory cytokines or other immune regulatory mechanisms [7]. IgD-CD38^dim B cells play a crucial role in regulating antibody production and maintaining immune tolerance [48]. In primary antiphospholipid syndrome, the dysfunction or abnormal distribution of B cell subsets is strongly associated with an increased risk of thrombosis [49]. Immune dysregulation, activation of thrombosis-related factors, and overexpression of B cell-activating factor can disrupt B cell tolerance, leading to an increase in antiphospholipid antibodies and promoting thrombosis [50]. CD45RA + CD8br (enhanced CD8 brightness) T cells represent a subtype of effector memory T cells with improved immune response capabilities. They protect the body by eliminating potential pathogens, controlling excessive inflammation, and providing protective effects [51]. CD4 on CD39 + CD4 + cells are a subtype of regulatory T cells, with CD39 being a negative regulatory molecule of adenosine signaling, which, by limiting excessive immune responses and maintaining endothelial cell function, may reduce the occurrence of DVT [52].

This study employs the two-sample MR approach, using data from large genomic cohorts with substantial sample sizes and strong statistical power. The study population includes over 400,000 VTE, 400,000 PE, and 360,000 DVT patients, along with a European population characterized by immunological features. Robust MR techniques were applied to mitigate the effects of confounders and horizontal pleiotropy, with FDR correction used to control false positives. Compared to traditional methods, this approach is more efficient, reduces confounder impact, and yields robust causal inferences.

However, this study has several limitations. First, the GWAS data primarily originate from European populations, which limits the external validity of the findings. Second, while MR provides robust estimates of population-level causal effects, it is inherently limited in its ability to characterize the dynamical changes of immune cell profiles across distinct disease progression stages. Additionally, potential confounding factors may persist in the bidirectional causal analysis. Although we mitigated traditional confounding bias by using genetic instrumental variable design, the GWAS data only adjusted for factors such as age, sex, genetic ancestry, and certain comorbidities. Specific data on allergic diseases and medication use (e.g., anticoagulant treatment) may not have been fully captured. This bias may arise from genetic correlations between the instrumental variables and these factors. For example, SNPs associated with immune cell characteristics may exhibit linkage disequilibrium with allergy susceptibility loci, thus affecting the accuracy of causal inferences. Future research should further explore the independence of the causal relationship between thrombosis and the immune system through colocalization analysis and drug-targeted MR.

Conclusion

This study clarifies the potential causal relationships between various immune cells and VTE, including PE and DVT. Additionally, reverse causality and other confounding factors have been minimized to some extent through our research. Our findings not only provide valuable insights for the treatment of VTE, PE, and DVT but also offer robust genetic evidence to advance research on the pathophysiology of thrombosis. These results may facilitate the development of novel therapeutic and preventive strategies.

Data availability

The data used in this study are freely available in public repositories. Summary statistics for venous thromboembolic diseases were obtained from the FinnGen consortium (https://finngen.gitbook.io/documentation/v/r10) and the GWAS Catalog (https://gwas.mrcieu.ac.uk/). All code utilized in this research is accessible, with the study’s original contributions detailed in both the article and its supplementary materials.

Abbreviations

VTE:

Venous thromboembolism

PE:

Pulmonary embolism

DVT:

Deep vein thrombosis

GWAS:

Genome-wide association study

MR:

Mendelian randomization

FDR:

False discovery rate

IVs:

Instrumental variables

SNPs:

Single nucleotide polymorphisms

AC:

Absolute cells

MFI:

Median fluorescence intensity

MP:

Morphological parameters

RC:

Relative cells

IVW:

Inverse variance weighted

OR:

Odds ratio

CI:

Confidence interval

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Acknowledgements

This study acknowledges the contribution of the FinnGen database and the publicly available GWAS catalog for providing the data.

Funding

This study was supported by the Affiliated Hospital of Jiangnan University, Wuxi, China.

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Authors and Affiliations

  1. Affiliated Hospital of Jiangnan University, Wuxi, 214122, China

    Wen Xiao, Danfeng Gu, Hailin Lu & Yang Zhao

  2. Wuxi School of Medicine, Jiangnan University, Wuxi, 214122, China

    Wen Xiao, Mingqi Zhang, Jiansu Liao & Tao Xu

Authors
  1. Wen Xiao
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  2. Danfeng Gu
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  3. Mingqi Zhang
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  4. Jiansu Liao
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  5. Tao Xu
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  6. Hailin Lu
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  7. Yang Zhao
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Contributions

XW conceived and designed the study and wrote the initial draft; ZMQ, LJS, and XT collected the data; LHL and ZY analyzed and interpreted the data; GDF revised the manuscript critically for important intellectual content and approved the final version to be submitted. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Danfeng Gu.

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All datasets used in this study are publicly available and do not require additional ethical approval.

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The authors report no conflicts of interest.

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Xiao, W., Gu, D., Zhang, M. et al. Causal relationship between immune cells and venous thromboembolism: a bidirectional two-sample Mendelian randomization study. Thrombosis J 23, 78 (2025). https://doi.org/10.1186/s12959-025-00754-4

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Keywords

Thrombosis Journal

ISSN: 1477-9560

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