Temporomandibular disorder (TMD) is characterized by symptoms including joint sounds, dysfunctional jaw movement, and preauricular pain. This condition has become a common and frequently occurring disease in the oral and maxillofacial regions (Monteiro et al., 2011; Diniz et al., 2012). The prevalence of TMD shows a notable range of variation globally, with figures reported between 25.5% and 36.0% across different populations (Fernandes et al., 2015). Particularly in the United States, the annual economic cost associated with TMD is substantial, exceeding 100 billion dollars (Lee et al., 2021). Moreover, it significantly affects patients’ quality of life and mental health (Bair et al., 2013; Moin Anwer et al., 2021). Thus, clarifying the risk factors associated with TMD is vital, as this could potentially aid in early prevention and consequently decrease its prevalence.

Previous studies have identified several risk factors for TMD, including oral parafunctions, osteoarthritis, and other painful conditions (e.g., chronic headaches) (Ferrillo et al., 2023; Minervini et al., 2023). Furthermore, the association between TMD and mental disorders like major depression (MD), bipolar disorder (BD) and schizophrenia (SCZ) is gradually gaining attention. TMD patients were more likely to suffer from MD, with a 4.33 times greater risk than those without TMD (Liou et al., 2023). Similar findings in Korean populations reported that depression patients exhibited a 3.07-fold higher risk of developing TMD (Heo et al., 2018). Other studies suggested a potential association between BD and TMD, but lacked causal evidence (Buenaver et al., 2012; Salinas Fredricson et al., 2022). Additionally, research indicated an elevated occurrence of TMD in individuals with SCZ in contrast to the control group (83.7% vs. 67.3%) (Gurbuz et al., 2009). However, other research reported that there was no correlation between MD, BD, SCZ, and TMD (Nifosì et al., 2007; Calixtre et al., 2014; Han et al., 2018). The limitations of the aforementioned studies hinder elucidation of the causal association, including limited sample sizes and observational designs, as well as the potential for confounding bias. Furthermore, the challenge arises from the comorbidity of various mental disorders, which complicates the assessment of the individual influence of a particular mental disorder on TMD through observational designs. To achieve clarity in the causal relationship, we should conduct further research.

To address potential biases in observational designs, this study employs Mendelian Randomization (MR), often referred to as a ‘natural randomized controlled trial. MR employs genetic variants to establish causal inferences regarding the relationships between exposure factors (i.e., MD, BD, and SCZ) and outcomes (i.e., TMD) (Chen et al., 2023). The single nucleotide polymorphisms (SNPs) of the exposure factors have been randomly allocated during gestation. The association can remain unaffected by postnatal confounding factors, which could introduce bias. This helps to overcome the constraints typically associated with observational studies (Emdin et al., 2017). A clear causal is beneficial to early intervention and clinical decision-making. This approach also offers a novel perspective on TMD prevention and treatment.

In this research, MR methodology was applied to explore the causal association between three varying mental disorders and the risk of TMD. Our findings reveal an intriguing association: there is a significant causal link between MD and TMD as genetically determined. However, the other two mental disorders (BD and SCZ) exert no causal effect on TMD. Therefore, it is imperative to evaluate the mental wellbeing of TMD patients in clinical practice, as this can contribute to enhancing their treatment and long-term prognosis.

This research sheds light on the connection between MD and TMD. Early observations help elucidate the link between MD and TMD (Giannakopoulos et al., 2010; De La Torre Canales et al., 2018; Sójka et al., 2019). An epidemiological study demonstrated that the prevalence of MD rises in tandem with the incidence of TMD pain-related injuries. The prevalence varied, showing a range from 16.7% in TMD individuals with no disability to 53.8% in those exhibiting high disability and severe restrictive injuries (Maísa Soares and Rizzatti-Barbosa, 2015). In a prospective study with 3,006 individuals, Kindler et al. (2012) confirmed that patients with MD exhibited a 1.95-fold higher risk of TMD than controls. Corresponding results were similarly observed in the studies conducted by Simoen et al. (2020). However, some studies contradicted this association (Pfau et al., 2009; Pizolato et al., 2013), highlighting the potential for discrepancies in findings due to differences in methodologies. To enhance data reliability and account for potential data category overlaps, we selected two distinct datasets (PGC and FinnGen). Our findings contribute to a broader comprehension of the effects of MD on TMD and offer additional causal evidence to inform clinical interventions.

However, the specific mechanism between depression and TMD still remains unclear. Differences in the regulation of the hypothalamus-pituitary-adrenal (HPA) axis in response to depressive symptoms could result in varying alterations in the body’s stress and alarm systems (Heim et al., 2008). These chronic regulatory processes can lead to ongoing muscle hyperactivity, progressively damaging the joint and ultimately manifesting as symptoms of TMD (Staniszewski et al., 2018). Depression may influence different gene polymorphisms, including COMT, ADRB2, and HTR1A genes, which are associated with chronic joint pain and TMD (Schwahn et al., 2012; Slade et al., 2013; Bonato et al., 2021). TNF-α, potentially serving as an inflammatory cytokine, mediates the relationship between MD and TMD. Elevated serum levels of TNF-α in individuals with MD could contribute, either directly or indirectly, to the development of TMD. Moreover, the heightened excitability of the HPA axis may, to some extent, affect the activity of the TNF-α system (Emshoff et al., 2000; Shrivastava et al., 2021). Additionally, if certain risk factors, such as genetic polymorphisms, exert differential impacts on muscle and joint discomfort, the detected specificity could stem from the distinct effect modification of depressive symptoms. Therefore, a more in-depth study is needed to unravel the complex mechanism between MD and TMD.

Our MR results indicate a lack of significant genetic influence on TMD risk in relation to BD or SCZ. In a prospective case-control study involving 366,437 Swedish individuals, Salinas Fredricson et al. (2022) reported a 1.40-fold higher risk of BD in patients with TMD than controls. However, there was no significant association with SCZ found in their study. Other observational research has indicated a potential correlation between SCZ and a heightened risk for TMD (Velasco-Ortega et al., 2005; de Araújo et al., 2014). Currently, our research does not confirm a direct causal relationship among BD, SCZ, and TMD. Nevertheless, the OR for BD is 1.22, which is greater than 1, and this result can still undergo further validation in a larger sample size.

There are several advantages to our research. Firstly, conducting randomized controlled trials to study disease development would be ethically problematic, as it would delay treatment for potentially ill patients. In contrast, MR analysis provides a more ethical approach, allowing us to utilize public data readily and control postnatal confounding factors in traditional observational studies. Secondly, our research, grounded in a European demographic, which helps reduce the potential of stratification bias. Thirdly, we utilize a large sample of GWAS datasets to enhance statistical power for both exposure and outcome. This includes the MD GWAS dataset (n = 480,359) and the TMD GWAS summary dataset (n = 211,023). Moreover, employing six different MR analysis methods, no substantial deviations across various methods were revealed, thus reinforcing the robustness of our results.

Nevertheless, some limitations need to be acknowledged. The further validation in diverse populations is warranted and not limited to European populations. Then, the causal relationship between mental illness and TMD can be influenced by various confounding factors. There is a complex genetic interplay between mental illness and other traits such as sleep quality, autoimmune diseases (e.g., rheumatoid arthritis), physical factors, and pain conditions (e.g., chronic headaches) (Sanders et al., 2013). Physical factors are genetically related to depression, and there is substantial genetic overlap with autoimmune diseases. These factors could potentially confound our research (Euteneuer et al., 2012; Fillingim et al., 2013; Ishigaki et al., 2022). In addition, the diagnostic criteria for TMD, as established by the DC/TMD, classify TMD into two main categories: painful disorders and joint disorders, with nine common diagnoses (Schiffman and Ohrbach, 2016; Khan et al., 2023). In future investigations these distinctions should be taken into account.

While the MR method offers advantages in estimating causality, multicenter randomized controlled trials with a large sample size continue to be the gold standard for confirming causality. Therefore, interpreting the results from MR studies should be objectivity.

In summary, we provide genetic evidence supporting a causal association between MD and TMD. Nonetheless, the underlying mechanism connecting MD and TMD warrants further investigation. Our study does not identify causal relationships between BD, SCZ, and TMD within the European population. Intervening MD at an early stage could potentially reduce the incidence of TMD. As a result, proactive interventions should be considered to mitigate the risk of TMD.