FormalPara Key Summary Points

Previous observational studies have linked periodontitis to migraine; however, the findings are inconclusive, and the causality of the link between periodontitis and migraine is unknown.

We have used a two-sample Mendelian randomization method to investigate the effect of periodontitis on migraine risk in this study.

This two-sample Mendelian randomization study has shown that there is no significant causal relationship between periodontitis and migraine.

It should be noted that early intervention with periodontal therapy is not always necessary in migraine prevention.

Introduction

Periodontitis (PD) is an infectious and inflammatory disease affecting the tooth-supporting tissue [1]. Plaque accumulation disrupts the bacterial ecosystem, leading to the formation of periodontal pockets, the recession of the gums, the destruction of the supporting connective tissue, and the loss of the tooth [2]. PD has a complex pathogenesis, with genetics playing a key role [3]. For instance, genetically identical monozygotic twins are more than twice as likely as dizygotic twins to develop early-onset PD [4]. Newly discovered evidence demonstrates that the genetic susceptibility of the host to PD is a major factor affecting the occurrence, progression, and prognosis of PD [5]. Although PD used to be considered a localized inflammatory disease, current evidence suggests that PD contributes to the body's overall inflammatory burden and even to neuroinflammation [6]; neuroinflammatory processes play a key role in the course of neurological disorders such as migraine [7]. Moreover, recent studies suggest that PD may play a role in migraine chronicity [2]. Migraine is a common intermittent neurologic disorder characterized by recurrent headache attacks that last for several hours and accompanying symptoms [8, 9]. As the headache progresses, it may be accompanied by a variety of autonomic, affective, cognitive, and sensory symptoms. In addition, the condition can be accompanied by abnormal skin sensitivity and muscle tenderness [8]. Migraine is not only caused by environmental factors but also caused by genetic factors [10]. Currently, the biological mechanisms underlying migraine heterogeneity are poorly understood [11], and further studies are needed to investigate the relationship between them.

Previous studies have reported an association between PD and migraine. A cross-sectional study by Leira et al. showed that PD was associated with migraine, but the association was significantly attenuated after adjusting for significant confounders, and the association estimates may still be biased by residual confounding [12]. Another cross-sectional study involving 138 subjects showed that PD independently increased serum calcitoninogen in subjects, suggesting that PD may be involved in the chronicity of migraine [13]. A longitudinal study in Taiwan identified 68,282 patients with PD with a significantly higher incidence of migraine in the PD cohort than in the non-PD cohort during a 13-year follow-up period, showing that PD was associated with an increased risk of subsequent migraine [14]. Although available observational studies show a positive association between PD and migraine [12,13,14], the likelihood of inferring causality is reduced because the study design does not ensure that exposure precedes outcome [15]. Therefore, it may be very challenging to exclude confounding factors and rule out reverse causality when observational studies are involved.

Mendelian randomization (MR) is an approach to account for observational bias and infer causal relationships [16, 17]. MR uses genetic variants as proxies for the exposures of interest to assess the causal relationship between exposure and outcome. It employs the natural randomness that occurs during the formation of an individual's genetic makeup, like the design of a randomized controlled trial (RCT), and uses instrumental variable analysis to estimate the impact of a modifiable exposure on an outcome from genetic variants [18]. Because genetic variations are set at conception, reverse causality has very little impact on MR. Additionally, MR is less prone to environmental confounding than traditional observational studies because genetic instrumental variables (IVs) are believed to affect the results exclusively through exposure and are independent of confounders [16]. To determine the causative relationship between PD and migraine, we conducted MR analyses on two samples using previously identified genome-wide association studies (GWAS) summary statistics.

Methods

The study was written in accordance with STROBE-MR guidelines [19]. The study protocol and details were not pre-registered.

Study Design

Exposure-related genetic variation (i.e., IV) was used to strengthen inferences about the potential causal relationship between exposure and outcome [16]. Because genetic variations are randomly assigned at conception, MR may not be influenced by confounding variables, disease processes, or measurement errors [16]. Genetic variations must satisfy three fundamental presumptions to be valid for IV (Fig. 1): (1) the "correlation" assumption, where IV is strongly associated with exposure (i.e., PD); (2) the "exclusion restriction" hypothesis, where IV affects outcome through exposure; and (3) the "independence" hypothesis, which states that IV is unrelated to confounding variables that relate exposure to outcome [20].

Fig. 1
figure 1

Schematic of Mendelian randomization study on the association of periodontitis with migraine. Mendelian randomization requires valid genetic instrumental variants satisfying three assumptions

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Data Sources

The Gene-Lifestyle Interactions in Dental Endpoints collaboration provided summary statistics for PD, the largest sample size to date, with a total of 17,353 clinical cases and 28,210 controls, based on 7 European descent cohort studies [21]. PD cases were classified using case definitions from the American Academy of Periodontology/Centers for Disease Control and Prevention case definitions, the Community Periodontal Index (CPI), or investigator reports of PD diagnosis, with additional inclusion criteria defined as two or more tooth surfaces with PPD ≥ 5 mm, or four or more with PPD ≥ 4 mm, two or more tooth surfaces with PPD ≥ 5.5 mm, or dental records of “gum surgery” [21]. We used data from the GWAS on genetic variants associated with migraine, which included 1,072 cases and 360,122 controls. This dataset contains European ancestry from the UK Biobank (UKB) cohort. The diagnostic criteria for migraine are based on the 10th edition of the International Classification of Diseases (recorded as "Diagnoses-main ICD10" in the UKB). To reduce potential bias due to demographic heterogeneity, all the above populations are of European origin. The data source characteristics are presented in Table 1. We conducted causal inference analyses to evaluate the association between PD and migraine using the available GWAS summary data from relevant single nucleotide polymorphisms (SNPs) (22).

Table 1 Genome-wide association studies used to obtain summary statistic for migraine and periodontitis
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The Choice of Instrumental Variables Based on Genetic Variations

We selected SNPs related to exposure at a significant threshold of p < 5 × 10–6 for PD and p < 5 × 10–6 for migraine to support the first supposition. If the SNP as IV contains missing data in the exposure or outcome summary, it was omitted. To ensure the SNPs were independent, linkage disequilibrium (LD) clustering was performed (LD R2 < 0.001, LD distance > 10,000 kb) [17]. The F statistic and the percentage of phenotypic variance explained by all the SNPs were used to confirm the first assumption [23].

Statistical Analyses

To ensure that the effect allele of each SNP was consistent between exposure and outcome in the MR analyses, the statistics were harmonized. The primary technique used to determine if PD and migraines are causally related was the inverse variance-weighted (IVW) method [24]. The likelihood of the MR relevance assumption may be diminished by a weak instrument-exposure association. As a result, we analyzed the instruments' F statistics and estimated the explained phenotypic variance. Although it is challenging to establish that the exchangeability and exclusion restriction assumptions in an MR study are correct, a sensitivity analysis might reveal potential violations of these assumptions. To assess the reliability of our findings, sensitivity analyses using the weighted median method [25], the MR-Egger method [26], and leave-one-SNP-out analysis [17] were carried out. We used the weighted median, a pleiotropy-robust approach to address the pleiotropy issue and to verify the second MR assumption, which states that IVs are not related to confounders [27]. We evaluated SNP heterogeneity in the IVW estimates using the Cochran's Q test (p < 0.1 shows heterogeneity) to confirm the third MR assumption, which states that the instrument is not linked to the outcome other than through its association with the exposure [28]. Testing for directional pleiotropy was performed using the MR-Egger intercept method. The absence of pleiotropy was indicated by an intercept centered at the origin with a 95% confidence interval (CI) including the null [29]. The leave-one-out test was used to determine whether the MR estimations were driven by a single SNP, and several polymorphism-enhanced MR methods were used [17]. All the MR analyses were carried out using R (v.4.0.3) and the "TwoSampleMR" package (version 0.5.6) [30]. The threshold for statistical significance was set at p < 0.05.

This article is based on previously conducted studies and does not include any new human or animal studies conducted by any of the authors.

Results

Characteristics of the Selected

After screening, 7 SNPs associated with PD (p < 5 × 10–6) were classified as valid IVs for migraine (R2 < 0.001; Supplementary Table 1). In the reverse MR analysis, 16 SNPs associated with migraine (p < 5 × 10–6) were classified as valid IVs for PD (R2 < 0.001; Supplementary Table 2). There were no SNPs associated with relevant confounders among these SNPs. The F statistic for all the included IVs was greater than 10, indicating that the SNPs used in our study are unlikely to be biased by weak instrumentation, and that the relevance assumption is unlikely to be violated.

Causal Relationship Between Periodontitis and Migraine Risk

Using the primary MR method, we found no significant causal relationship between PD and migraine using the IVW method [OR (odds ratio) = 1.000; 95% CI − 0.001 to 0.001; p = 0.645]. Using other MR methods such as the weighted median method (OR = 1.000; 95% CI − 0.001 to 0.002; p = 0.599) and the MR-Egger estimation method (OR = 1.000; 95% CI − 0.001 to 0.002; p = 0.670) also provided similar results, indicating a lack of causal relationship between PD and migraine (Table 2; Fig. 2). Meanwhile, the MR-Egger regression analysis revealed that no potential pleiotropic effect exists for the variants used in constructing the genetic instruments (p = 0.67) (Table 3). Cochran's Q test revealed that there was no substantial heterogeneity or horizontal pleiotropy (Table 3). There was no notable pleiotropy, as shown by the weighted linear regression line's intercept, which was very close to zero (Table 3). Regarding SNP compliance, we performed a leave-one-out sensitivity analysis, which showed that no individual SNP had a strong effect on the overall effect (Fig. 3). In addition, the funnel plot showed no asymmetry, indicating that directional horizontal pleiotropy was not detected (Fig. 3). The scatter plots of SNP–outcome associations versus SNP–exposure associations failed to identify any leverage points with significant influence (Fig. 3). These findings revealed the strong estimate and weak bias of the MR analysis. Using the PhenoScanner, we confirmed that no genetic instruments of PD or migraine were associated with any potential confounding factors. Low or no heterogeneity, a lack of evidence for potential confounding SNPs, and results that are comparable to reliable assessments of pleiotropy all implicitly support the MR hypotheses (2) and (3).

Table 2 Estimates based on Mendelian randomization for the relationship between genetically instrumented periodontitis and migraine
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Fig. 2
figure 2

Mendelian randomization estimates for the relationship between genetically instrumented periodontitis and migraine. PD periodontitis, CI confidence interval, IVW inverse variance weighted, N.SNPs number of SNPs used in MR, OR odds ratio, MR Mendelian randomization

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Table 3 The heterogeneity and horizontal pleiotropy of individual SNPs
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Fig. 3
figure 3

Complementary MR analyses of periodontitis with migraine. A Funnel plot of the causal estimates for PD on migraine; B leave-one-out plot of the causal estimates for PD on migraine; C scatter plot of the causal estimates for PD on migraine; D funnel plot of the causal estimates for migraine on PD; E leave-one-out plot of the causal estimates for migraine on PD; F scatter plot of the causal estimates for migraine on PD

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However, no causal relationships between migraine and PD were discovered when it was employed as an outcome measure (Table 2). Furthermore, the sensitivity analysis found no evidence of weak instrument bias or horizontal pleiotropic bias (Table 3). Variant-specific causal estimates were further visualized in funnel plots, scatter plots, and forest plots, indicating no significant heterogeneity and pleiotropy among migraine SNPs (Fig. 3). Collectively, these results suggested that no causal association exists between PD and migraine.

Discussion

This was the first MR analysis to use a two-sample MR method to investigate whether genetically predicted PD is causally related to migraine. We found no causal relationship between PD and migraine in this two-sample MR investigation involving persons of European heritage.

The association between PD and migraine remains inconclusive despite numerous investigations. Although two cross-sectional studies have suggested that PD is associated with migraine [12, 13], the failure of the study design to guarantee that exposure precedes outcome reduces the likelihood of concluding cause-and-effect relationships [15]. Thus, longitudinal research may provide stronger evidence of the time-dependent association than cross-sectional studies, which often only provide limited insight into temporal ordering and allow for bidirectional causality. One longitudinal study in Taiwan associated PD with an increased risk of migraine; however, the study population was limited and did not exclude the effect of taking over-the-counter analgesics, and may also have been influenced by relative confounders, such as dietary practices, environmental influences, smoking, drinking, and way of life [14]. Our MR estimates contradict existing observational studies, firstly, possibly because the previously observed association between PD and migraine is biased or confounded by certain confounding factors, and secondly, because observational studies are insufficient to demonstrate a causal relationship between PD and migraine.

Calcitonin gene-related peptide (CGRP) is considered a key factor in the pathophysiology of migraine [31]; however, two case–control studies based on European populations have provided conflicting evidence for the involvement of CGRP in the association between PD and migraine [32, 33]. One RCT has demonstrated elevated CGRP levels in patients with PD and migraine compared to controls, suggesting that CGRP is involved in the pathogenesis of both diseases [33], whereas a more recent RCT has shown that CGRP levels were reduced in patients with PD and migraine, suggesting that CGRP may prevent PD and be involved in the pathogenesis of migraine. Thus, there is inconclusive evidence regarding the association between PD and migraine [32], and the available observational studies are insufficient to refute the findings of this two-sample MR study. Furthermore, because observational studies are susceptible to confounding factors and reverse causality, and are somewhat biased, they are not sufficient to establish a causal relationship between PD and migraine. Therefore, we conclude that there is no causal relationship between PD and the risk of migraine headaches.

Periodontal inflammation that affects the gingival tissue releases several inflammatory mediators that may be involved in the development of migraine attacks. PD may result from an interaction between a host and periodontal pathogens, like Porphyromonas gingivalis, Porphyromonas conidia, or Actinobacteria, to produce cytokines and acute phase reactants, like interleukin-1 and -6, tumor necrosis factor-α, and C-reactive protein, that are spread throughout the body by endotoxemia. Additionally, this low-grade chronic inflammation may promote the overexpression of neurogenic biomarkers, such as CGRP, substance P, and neurokinin A, in patients with chronic migraine who are experiencing episodes [2]. These inflammatory pathways have not been conclusively demonstrated to be involved in the causal relationship between PD and migraine, and some comorbidities likely share this inflammatory pathway. In addition, several studies have shown that impaired endothelial function in patients with migraine is associated with chronic low-grade systemic inflammation caused by PD [34, 35]. Patients with PD have elevated levels of the vascular wall-damaging factor fibrinogen, whereas endothelial progenitor cells, which are important for endothelial regeneration and repair of damaged vessels, are reduced; similar results have been reported among patients with migraine [2]. However, there is no definitive evidence from in vivo experiments to demonstrate this association, and some shared inflammatory pathways may contribute to the link between PD and migraine. Consequently, there is no genetically predicted causal relationship between PD and migraine.

The present MR analysis made use of genetic information as an instrumental variable and the advantage of a large sample size. Notably, the MR analysis allowed for the assessment of the causal relationship between migraine and PD. In addition, this approach is less susceptible to bias from reverse causality and confounding compared to conventional observational research [36]. The estimates for PD and migraine SNP effects were acquired from European (ancestry) research, reducing the likelihood of population stratification bias and boosting the plausibility of the two-sample MR assumption. Meanwhile, our study has several limitations. First, in the GWAS summary statistics for PD and migraine, we included only participants of European ancestry, so it is unclear whether our findings also hold for those with non-European heritage. Further research would be necessary to determine whether the relationship between PD and the risk of migraine is generalizable to other ethnic groups. Second, PD was determined using diverse criteria in the studies that contributed to the GWAS summary statistics, and, in some studies, the participants self-reported having the condition. Finally, given that migraine cases were characterized by ICD codes, it is likely that some controls were misclassified and that there was a certain degree of selection bias.

Conclusions

Our MR study suggests that there is no causal relationship between PD and migraine or migraine and PD, although the findings from observational studies may not be consistent with our results. It should be noted that early intervention with periodontal therapy is not always necessary in migraine prevention.