Exploring the Two-Way Link between Migraines and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization Study

Abstract

Background The objective of this study is to utilize Mendelian randomization to scrutinize the mutual causality between migraine and venous thromboembolism (VTE) thereby addressing the heterogeneity and inconsistency that were observed in prior observational studies concerning the potential interrelation of the two conditions.

Methods Employing a bidirectional Mendelian randomization approach, the study explored the link between migraine and VTE, incorporating participants of European descent from a large-scale meta-analysis. An inverse-variance weighted (IVW) regression model, with random-effects, leveraging single nucleotide polymorphisms (SNPs) as instrumental variables was utilized to endorse the mutual causality between migraine and VTE. SNP heterogeneity was evaluated using Cochran's Q-test and to account for multiple testing, correction was implemented using the intercept of the MR-Egger method, and a leave-one-out analysis.

Results The IVW model unveiled a statistically considerable causal link between migraine and the development of VTE (odds ratio [OR] = 96.155, 95% confidence interval [CI]: 4.342–2129.458, p = 0.004), implying that migraine poses a strong risk factor for VTE development. Conversely, both IVW and simple model outcomes indicated that VTE poses as a weaker risk factor for migraine (IVW OR = 1.002, 95% CI: 1.000–1.004, p = 0.016). The MR-Egger regression analysis denoted absence of evidence for genetic pleiotropy among the SNPs while the durability of our Mendelian randomization results was vouched by the leave-one-out sensitivity analysis.

Conclusion The findings of this Mendelian randomization assessment provide substantiation for a reciprocal causative association between migraine and VTE within the European population.

Keyword

Mendelian randomization - migraine - venous thromboembolism - bidirectional - causality

Introduction

Venous thromboembolism (VTE) encompasses both deep vein thrombosis and pulmonary embolism,[1] ranking third globally as a prevalent vascular disorder associated with mortality.[2] This increases the mortality risk for patients and compounds the financial burden on health care services. Hence, the ongoing evaluation and assessment of VTE risk in clinical settings are crucial.

Migraine, characterized by recurrent episodes of severe unilateral headaches accompanied by pulsating sensations and autonomic symptoms, affects approximately one billion individuals worldwide.[3] Several research studies indicate an increase in VTE incidence among migraine sufferers.[4] [5] [6] [7] [8] Hence, there is a significant need for further investigation to elucidate the causal relationship between VTE and migraines.

Mendelian randomization (MR) is a methodology that utilizes genetic variants as instrumental variables (IVs) to explore the causal association between a modifiable exposure and a disease outcome.[9] By leveraging the random allocation and fixed nature of an individual's alleles at conception, this approach helps alleviate concerns regarding reverse causality and environmental confounders commonly encountered in traditional epidemiological methods.

In order to mitigate confounding factors and ensure robust outcomes, this investigation adopts a pioneering approach by utilizing MR to explore the genetic-level causal correlation between migraine and VTE. To the best of our knowledge, no previous study has employed this method to examine the association between these two pathological conditions, thereby lending an innovative and cutting-edge aspect to this research.

Materials and Methods

Research Methodology

A rigorous bidirectional two-sample MR examination was implemented to probe the causal link between migraine and VTE risk, subsequent to a meticulous screening mechanism. For achieving credible estimations of MR causality, efficacious genetic variances serving as IVs must meet three central postulates: (I) relevance assumption, asserting that variations must demonstrate intimate association with the exposure element; (II) independence/exchangeability assumption, demanding no correlations be exhibited with any measured, unmeasured, or inconspicuous confounding elements germane to the researched correlation of interest; and (III) exclusion restriction assumption, maintaining that the variation affects the outcome exclusively through the exposure, devoid of alternative routes.[10] [11] A single nucleotide polymorphism (SNP) refers to a genomic variant where a single nucleotide undergoes alteration at a specific locus within the DNA sequence. SNPs were employed as IVs in this study for estimating causal effects. The study's design is graphically portrayed in [Fig. 1], emphasizing the three fundamental postulates of MR. These postulates are of the utmost importance in affirming the validity of the MR examination and ensuring the reliability of the resultant causal inferences.[12]

Fig. 1 This figure illustrates the research methodology for the bidirectional Mendelian randomization analysis concerning migraine and VTE. Assumption I: relevance assumption; Assumption II: independence/exchangeability assumption; Assumption III: exclusion restriction assumption.

Data Sources

Our SNPs are obtained from large-scale genome-wide association studies (GWAS) public databases. The exposure variable for this study was obtained from the largest migraine GWAS meta-analysis conducted by the IEU Open GWAS project, which can be accessed at https://gwas.mrcieu.ac.uk/datasets.[13] [14] The outcome variable was derived from the largest VTE GWAS conducted by FinnGen, available at https://www.finngen.fi.[15] A comprehensive overview of the data sources used in our study can be found in [Table 1].

Table 1 Description of GWAS used for each phenotype

Variable	Sample size	ID	Population	Database	Year
Migraine	337159	ukb-a-87	European	IEU Open GWAS project	2017
VTE	218792	finn-b-I9_VTE	European	FinnGen	2021

Abbreviations: GWAS, genome-wide association studies; VTE, venous thromboembolism.

Note: Basic information of GWAS for migraine and VTE is displayed in this table.

The variances in genetic variations and exposure distributions across diverse ethnicities could potentially result in spurious correlations between genetic variants and exposures.[16] Consequently, the migraine and VTE GWAS for this study were sourced from a homogeneous European populace to circumvent such inaccurate associations. It is crucial to highlight that the data harvested from public databases were current up to March 31, 2023. Given the public nature of all data utilized in our study, there was no necessity for further ethical approval.

Filtering Criteria of IVs

To select appropriate SNPs as IVs, we followed standard assumptions of MR. First, we performed a screening process using the migraine GWAS summary data, applying a significance threshold of p < 5 × 10⁻⁸ (Assumption I). To ensure the independence of SNPs and mitigate the effects of linkage disequilibrium, we set the linkage disequilibrium coefficient (r ²) to 0.001 and restricted the width of the linkage disequilibrium region to 10,000 kb. PhenoScanner (http://www.phenoscanner.medschl.cam.ac.uk/) serves as a versatile tool, enabling users to explore genetic variants, genes, and traits linked to a wide spectrum of phenotypes.[17] [18] Utilizing PhenoScanner v2, we ruled out SNPs linked with potential confounding constituents and outcomes, thereby addressing assumptions II and III. Subsequently, we extracted the relevant SNPs from the VTE GWAS summary data, ensuring a minimum r ² > 0.8 and replacing missing SNPs with highly linked SNPs. We excluded SNPs without replacement sites and palindromic SNPs and combined the information from both datasets. Finally, we excluded SNPs directly associated with VTE at a significance level of p < 5 × 10⁻⁸ and prioritized IVs with an F-statistic [F-statistic = (β/SE)2] > 10 to minimize weak instrument bias.[19]

Statistical Analysis

For our analysis, we employed the inverse-variance weighted (IVW) random-effects regression model to assess the causal relationship between migraine and VTE, utilizing SNPs as IVs. This approach allowed us to directly calculate the causal effect using summary data, eliminating the need for individual-level data. To assess SNP heterogeneity, we conducted Cochran's Q test and, in the presence of heterogeneity, relied on the results of the IVW model. To examine the presence of pleiotropy, we utilized the MR-Egger method and conducted leave-one-out analysis. All statistical analyses were performed using the TwoSampleMR package in R 4.2.2 software, with a significance level set at α = 0.05.

Results

In the present investigation, we capitalized on a bidirectional two-sample MR analysis in individuals of European descent to scrutinize the potential causative correlation between migraines and VTE risk. Our investigation implies a potential bidirectional pathogenic relationship between migraines and the risk of VTE, as supported by the specific analysis results detailed in [Table 2].

Table 2 Mendelian randomization regression causal association results

Exposures	SNPs (no.)	Methods	β	SE	OR (95% CI)	p
Migraine	11	IVW	4.566	1.580	96.155 (4.342–2129.458)	0.004
VTE	12	IVW	0.002	0.001	1.002 (1.000–1.004);	0.016
		Simple mode	0.003	0.001	1.003 (1.000–1.006)	0.047

Abbreviations: CI: confidence interval; IVW, inverse variance weighting; OR, odds ratio; SE, standard error; SNPs, single nucleotide polymorphisms; VTE, venous thromboembolism.

Note: This table displays the causal relationship between migraine leading to VTE and VTE leading to migraine.

Mendelian Randomization Analysis

During the IV screening process, it was identified that SNP r10908505 was associated with body mass index (BMI) in VTE. Considering the established association between BMI and VTE,[1] [15] this violated Assumption III and the SNP was subsequently excluded. The VTE dataset ultimately consisted of 11 SNPs, with individual SNP F-statistics ranging from 29.76 to 96.77 (all >10), indicating a minimal potential for causal associations to be confounded by weak IV bias ([Supplementary Table S1], available in the online version). The IVW model revealed that migraine was a statistically significant risk factor for the onset of VTE (odds ratio [OR] = 96.155, 95% confidence interval [CI]: 4.3422–129.458, p = 0.004) ([Table 2], [Fig. 2A]). The scatter plot ([Fig. 2B]) and funnel plot ([Fig. 2C]) of migraine demonstrated a symmetrical distribution of all included SNPs, suggesting a limited possibility of bias affecting the causal association. The Cochran's Q test, conducted on the MR-Egger regression and the IVW method, yielded statistics of 5.610 and 5.973 (p > 0.05), indicating the absence of heterogeneity among the SNPs ([Supplementary Table S2], available in the online version). These findings suggest a positive correlation between the strength of association between the IVs and migraine, satisfying the assumptions of IV analysis. The MR-Egger regression analysis showed no statistically significant difference from zero for the intercept term (p = 0.5617), indicating the absence of genetic pleiotropy among the SNPs ([Supplementary Table S3], available in the online version). Additionally, the leave-one-out analysis revealed that the inclusion or exclusion of individual SNPs did not substantially impact the estimated causal effects, demonstrating the robustness of the MR results obtained in our investigation ([Fig. 2D]).

Fig. 2 This figure explores the correlation between migraine risk and VTE, validating the presence of heterogeneity and pleiotropy. (A) The forest plot displays individual IVs, with each point flanked by lines that depict the 95% confidence interval. The effect of SNPs on the exposure (migraine) is shown along the x-axis, whereas their impact on the outcome (VTE) is presented on the y-axis. A fitted line reflects the Mendelian randomization analysis results. (B) A scatter plot visualizes each IV, with the SNP effects on both exposure and outcome similar to that of the forest plot. Again, a fitted line represents the Mendelian randomization results. (C) The funnel plot positions the coefficient β_IV from the instrumental variable regression on the x-axis to demonstrate the association's strength, while the inverse of its standard error (1/SE_IV ^†) on the y-axis indicates the precision of this estimate. (D) A leave-one-out sensitivity analysis is shown on the x-axis, charting the estimated effects from the Mendelian randomization analysis. With each SNP associated with migraine successively excluded, the analysis recalculates the Mendelian randomization effect estimates, culminating with the “all” category that encompasses all considered SNPs. IV, instrumental variable; SNP, single nucleotide polymorphisms; VTE, venous thromboembolism; SE, standard error. ^†SE is the standard error of β.

Reverse Mendelian Randomization Analysis

Upon screening for IVs in migraine patients, SNP rs6060308 was excluded due to its association with education[20] [21] and violation of Assumption III. The final migraine dataset comprised 13 SNPs, with individual SNP F-statistics ranging from 30.60 to 354.34, all surpassing the threshold of 10 ([Supplementary Table S4], available in the online version). Both the IVW and simple models supported VTE as a risk factor for migraine. The IVW analysis yielded an OR of 1.002 (95% CI: 1.000–1.004, p = 0.016), while the simple model yielded an OR of 1.003 (95% CI: 1.000–1.006, p = 0.047) ([Table 2], [Fig. 3A]). The scatter plot ([Fig. 3B]) and funnel plot ([Fig. 3C]) exhibited symmetrical distributions across all included SNPs, indicating minimal potential for biases affecting the causal association. Heterogeneity among SNPs was observed through the Cochran's Q test of the IVW method and MR-Egger regression, with Q statistics of 18.697 and 20.377, respectively, both with p < 0.05 ([Supplementary Table S2], available in the online version). Therefore, careful consideration is necessary for the results obtained from the random-effects IVW method. MR-Egger regression analysis revealed a nonsignificant difference between the intercept term and zero (p = 0.3655), suggesting the absence of genetic pleiotropy among the SNPs ([Supplementary Table S3], available in the online version). Additionally, the leave-one-out analysis demonstrated that the inclusion or exclusion of individual SNPs had no substantial impact on the estimated causal effect ([Fig. 3D]).

Fig. 3 (A–D) This figure presents the relationship between VTE risk and migraine, also verifying heterogeneity and pleiotropy through similar graphic representations as detailed for [Fig. 2], but with the exposure and outcome reversed—SNPs' effect on VTE and outcome on migraine. SNP, single nucleotide polymorphisms; VTE, venous thromboembolism.

Discussion

VTE constitutes a grave health hazard to patients, necessitating rigorous clinical surveillance. Distinct from common VTE risk factors such as cancer,[22] diabetes,[23] lupus,[24] and antiphospholipid syndrome,[25] migraines remain absent from prevalent VTE guidelines or advisories. The MR findings from our research provide first-of-its-kind evidence of a causal nexus between migraines and VTE in individuals of European descent, signaling that migraines potently predispose individuals to VTE (IVW OR = 96.155, 95% CI: 4.342–2129.458), while VTE presents a weak risk factor for migraines (IVW OR = 1.002, 95% CI: 1.000–1.004). Given the robustness of the IVW analysis, the MR analysis is considered reliable.

Our MR analysis discloses a potential causal association between individuals suffering from migraines and VTE incidence, with a risk rate 96.155 times higher in comparison to nonmigraine sufferers. Previous observational endeavors investigating VTE risk amidst migraine patients have been scant and have yielded discordant outcomes, complicating the provision of clinical directives.[26] [27] In a longitudinal inquiry with a 19-year follow-up, Adelborg et al discerned a heightened VTE risk in individuals afflicted with migraines.[4] Peng et al's prospective clinical study unveiled a more than double VTE risk increase in migraine patients during a 4-year follow-up.[5] Schwaiger et al's cohort study, incorporating 574 patients aged 55 to 94, observed a significant escalation in VTE risk among elderly individuals with migraines.[6] [28] Bushnell et al uncovered a tripled VTE risk during pregnancy in migraine-affected women.[29] Although these studies validate a potential correlation between migraines and VTE, their persuasiveness is restricted due to other prominent VTE risk factors (such as advanced age and pregnancy) and contradicting findings in existing observational studies. For instance, Folsom et al observed no significant correlation between migraines and VTE risk in elderly individuals, contradicting Schwaiger's conclusion.[7] However, he clarified that the cohort incorporated in his study did not undergo rigorous neurological migraine diagnosis, possibly leading to confounding biases and generating findings that contradict other scholarly endeavors.[7] These contradictions originate from observational studies examining associations rather than causal relationships, invariably involving a confluence of various confounding factors. MR, leveraging SNPs as IVs to ascertain the causal link between migraines and VTE risk, can eliminate other confounding elements resulting in more reliable outcomes. Based on this finding, monitoring VTE risk among migraine patients in clinical practice is recommended.

The reverse MR analysis reveals that compared to non-VTE patients, those with VTE among individuals of European ancestry exhibit a marginally heightened susceptibility to migraines, with a relative risk of 1.02 (as per the IVW method). This discovery concurs with the existing void in research on migraines among VTE patients. Thus, even with slightly increased risks of migraines in VTE patients, we do not advocate for heightened concern regarding the emergence of migraines among this patient group.

Our endeavor seeks to offer a preliminary examination of the potential mechanisms underlying the interplay between migraines and VTE. The incidence of VTE habitually involves Virchow's triad, encompassing endothelial damage, venous stasis, and hypercoagulability.[30] On the genetic association front, the SNPs rs9349379 and rs11172113, acting as IVs for migraines, display relevance to the mechanisms underpinning VTE. Prior research earmarks the gene corresponding to rs9349379, PHACTR1 ([Supplementary Table S1], available in the online version), as a catalyst for the upregulation of EDN1.[31] Elevated EDN1 expression is associated with increased VTE susceptibility,[32] and EDN1 inhibition can diminish VTE incidence,[33] potentially through Endothelin 1-mediated vascular endothelial inflammation leading to thrombus formation.[34] The SNP rs11172113 corresponds to the gene LRP1 ([Supplementary Table S1], available in the online version).[35] LRP1 can facilitate the upregulation of FVIII, culminating in an increase in plasma coagulation factor VIII,[36] thereby leading to heightened blood coagulability and an associated elevated VTE risk.[37] While various studies propose divergent mechanisms, they collectively signal that migraines can instigate a hypercoagulable state, thereby promoting the onset of VTE. The SNPs serving as IVs for VTE did not unveil any association with the onset of migraines. This corroborates our MR analysis outcomes, indicating that VTE is merely a weak risk factor for migraines.

Strengths and Limitations

This study possesses several notable strengths. First, it fulfills all three assumptions of MR, minimizing the influence of confounding factors and addressing the limitations inherent in observational studies, thus yielding more robust findings. We carefully excluded two SNPs (rs10908505 and rs6060308) that could potentially impact the results. In addition, we employed PhenoScanner v2 to comprehensively probe confounding variables related to VTE, as described earlier, and factors associated with migraines, such as acute migraine medication overuse, obesity, depression, stress, and alcohol, leading to the subsequent exclusion of relevant SNPs. This ensured that the selected SNPs specifically captured the causal effects and eliminated potential confounding effects from polygenic associations with disease susceptibility. Second, the study sample was restricted to individuals of European descent, minimizing the potential bias introduced by population heterogeneity and enhancing the internal validity of the findings. Third, the use of strongly correlated SNPs (F >> 10) in both migraine → VTE and VTE → migraine analyses enhances the validity of the IVs. Finally, this study pioneers the hypothesis of a plausible causal association between VTE and an elevated susceptibility to migraines, offering novel insights into their potential relationship.

Nonetheless, it is essential to acknowledge the presence of several limitations in this study that warrant consideration. First, the study participants were predominantly of European ancestry, which, although it avoids the influence of ethnicity on the results, limits the generalizability of the findings to other ethnic groups. Second, our study solely establishes the causal relationship between migraine and VTE risk without elucidating the underlying mechanisms. Third, we only selected SNPs that met the stringent genome-wide significance level (p < 5 × 10⁻⁸), potentially excluding truly relevant variations that did not reach this threshold. Lastly, as our MR analysis relies on publicly available summary statistics data, the lack of detailed clinical information hinders subgroup analysis.

Conclusion

In essence, the bidirectional Mendelian randomization analysis, conducted within the European populace, indicates the presence of a relatively strong causal correlation between migraines and VTE, while the causative relationship between VTE and migraines appears exceedingly faint. These deductions imply the need for rigorous monitoring of VTE in individuals of European descent suffering from migraines, thus requiring synergistic effort between general physicians and neurologists. Nevertheless, VTE patients should refrain from undue worries concerning the incidence of migraines. Further, we stress the importance of harnessing information gleaned from a wide array of observational studies and controlled experiments to strengthen the credibility of drawn causal inferences. This is pivotal in establishing a mutual corroboration with the results obtained through MR analysis. Hence, the exigency for additional stringent observational studies and comprehensive laboratory research prevails to corroborate the conclusions made in this study.

Conflict of interest

None declared.

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Publication History

Received: 10 June 2023

Accepted: 10 April 2024

Accepted Manuscript online:
24 April 2024

Article published online:
20 May 2024