This study used a 2-sample MR design, relying exclusively on publicly accessible data for all analyses. We meticulously adhered to the recommendations presented in the Strengthening the Reporting of Observational Studies in Epidemiology-Mendelian Randomization (STROBE-MR) guidelines, ensuring a comprehensive and rigorous reporting approach.

This study is a secondary analysis of publicly available genome-wide association study (GWAS) summary statistics obtained from the Integrative Epidemiology Unit OpenGWAS database [12]. As no new individual-level data were collected and no direct human participation was involved, ethical approval from an institutional review board was not required. The original GWASs adhered to their respective ethical guidelines and received necessary approvals. Since the study exclusively used deidentified, publicly available data, informed consent was not applicable; however, the original studies obtained informed consent from participants at the time of data collection and explicitly permitted secondary data analysis without additional consent. All data used in this study were fully anonymized, ensuring participant confidentiality, and no personally identifiable information was accessed, stored, or analyzed. In accordance with data protection regulations and ethical standards, strict measures were taken to maintain privacy and confidentiality. As no human participants were directly involved, no compensation was provided. Additionally, this study does not include any identifiable images or figures.

We procured summary-level data for COVID-19 susceptibility (n=1,683,768), COVID-19 hospitalization (n=1,882,773), and COVID-19 severity (n=1,388,342) from the Integrative Epidemiology Unit OpenGWAS database [12]. This database offers extensive GWAS summary statistics encompassing a diverse array of traits and outcomes.

The data on COVID-19 susceptibility included 38,984 individuals, comprising individuals diagnosed with COVID-19 through laboratory confirmation of SARS-CoV-2 infection, electronic health records using International Classification of Diseases (ICD) codes or physician notes, or self-reported cases. For COVID-19 hospitalization, 9986 individuals were included, while COVID-19 severity encompassed 5101 individuals categorized as being in an extremely critical condition, which included individuals who experienced mortality or required advanced respiratory support [13-15].

Detailed information regarding the genetic variants associated with these COVID-19-related outcomes is presented in 3/7/2025 [16], offering a comprehensive overview of the exposure variables used in our MR analysis.

The outcome data for GD were extracted from publicly available summary statistics, involving a total of 2176 GD cases and 210,277 controls (GWAS ID: bbj-a-123). The cases represented individuals hospitalized for GD, and the control group consisted of individuals from cohorts without identified cases. The genetic instruments used for GD in this MR study were derived from these data, facilitating a comprehensive evaluation of the causal relationship between GD and pertinent genetic variations.

For constructing genetic instruments for each exposure, we used a rigorous approach. We identified single nucleotide polymorphisms (SNPs) displaying significant associations with the respective exposure at a genome-wide significance threshold (P<5×10⁻⁶), which, while less stringent than the conventional threshold (P<5×10^–⁸), was chosen to balance instrument strength and the number of available SNPs. These SNPs underwent linkage disequilibrium clumping to remove highly correlated SNPs (r²≥0.001). Our reference population was drawn from the European cohort within the 1000 Genomes Project, which may limit the generalizability of our findings to non-European populations. To ensure consistency in effect sizes and address issues related to palindromic SNPs, we harmonized SNP-exposure and SNP-GD associations. In cases where specific SNPs were missing in the GD GWAS dataset, we used proxy SNPs (r²>0.8). To mitigate potential bias from weak instruments, we performed F statistic calculations and conducted multiple sensitivity analyses, including leave-one-out analysis and MR-Egger regression. The processes of SNP extraction from GWAS summary-level data, linkage disequilibrium clumping, and harmonization were executed using the TwoSample MR package in R version 4.3.0 (R Core Team) [17,18]. The strength of the instrumental variables was evaluated using the F statistic, computed as follows: F = (R²/K)/[(1−R²) (N−K−1)], where R² denotes the variance explained by the instruments, K is the number of instruments, and N is the sample size [19].

Using a 2-sample MR approach, we estimated the causal effects of COVID-19 susceptibility and its severity on GD. The primary MR analysis used the inverse-variance weighting (IVW) method, assuming that the genetic instruments collectively satisfy the core MR assumptions. In addition to the primary MR analysis, we conducted supplementary sensitivity analyses, including MR-Egger, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. These methods enhance robustness against potential pleiotropic effects by relaxing certain MR assumptions. To assess horizontal pleiotropy, we used the intercept term from MR-Egger regression, where an intercept P value exceeding .05 indicated an absence of pleiotropy. Furthermore, we applied MR-PRESSO as a supplementary method to detect and exclude outlier genetic instruments with pleiotropic effects, subsequently estimating causal effects. All tests were 2-sided and executed using the TwoSampleMR and MR-PRESSO packages in R version 4.3.0. A significance threshold was set at P<.05. Since our analysis exclusively used publicly available data, no ethical approval from a local committee was sought.

In this MR study, we extensively explored the potential causal relationships between COVID-19 susceptibility, COVID-19 hospitalization, and COVID-19 severity in relation to GD. Using a variety of MR methods, we aimed to provide a comprehensive understanding of these relationships. Our study results underscore the absence of a causal link between COVID-19 susceptibility and GD. Recent research continues to unveil the intricate interplay between autoimmune diseases and viral infections. For example, a study conducted by Widhani et al [20] delved into the potential associations between viral infections, including COVID-19, and autoimmune thyroid diseases, further corroborating our findings. Additionally, the work of Smith and Hegedüs [21] has provided in-depth insights into the pathogenesis of GD, emphasizing its multifactorial nature. These recent studies lend robust support to our research. Furthermore, investigations into the relationship between COVID-19 and autoimmune diseases have expanded in recent years. A systematic review by Tutal et al [22] examined the impact of autoimmune thyroid diseases on the severity of COVID-19, enriching our understanding of the bidirectional influences between these health conditions. To provide a broader clinical context, we have integrated evidence on how COVID-19 susceptibility and outcomes differ across other autoimmune diseases, which highlights the need for more nuanced investigations beyond GD alone [23].

Similarly, we found that COVID-19 hospitalization does not significantly increase the risk of GD. The consistency of this result across various MR methods suggests that COVID-19 hospitalization is not a causal risk factor for GD. This conclusion is pivotal for understanding the etiology of GD and its relationship with other health conditions. Recent research has provided further insights into the connection between COVID-19 and autoimmune thyroid diseases. For example, a study by Fallahi et al [24], conducted within the past 5 years, investigated the impact of COVID-19 hospitalization on the development of autoimmune thyroid diseases, including GD. The study used a large-scale patient database and used statistical methods to evaluate the risk of developing autoimmune thyroid diseases after COVID-19 hospitalization. Their findings, which align with our MR results, indicated that COVID-19 hospitalization was not significantly associated with an increased risk of GD or other autoimmune thyroid diseases. This further supports the critical importance of recognizing that COVID-19 hospitalization itself does not have a direct causal role in the development of GD. Furthermore, we examined the relationship between COVID-19 severity and the risk of developing GD. Our study revealed that COVID-19 severity does not contribute to the onset of GD. This finding provides important insights into the genetic and environmental factors influencing GD’s pathogenesis. A recent study by Bostan and colleagues [25] explored the genetic mechanisms underlying the development of GD in individuals with severe COVID-19. Their research highlighted the role of genetic susceptibility in the development of GD among those with severe COVID-19, adding to our understanding of the complex interaction between COVID-19 and autoimmune thyroid diseases.

Moreover, recent research has extensively explored the associations between COVID-19 and thyroid-related conditions. Studies have indicated that COVID-19 infection can influence thyroid function, potentially leading to hyperthyroidism or thyrotoxicosis in certain individuals, further emphasizing the potential link between COVID-19 and thyroid diseases. However, the specific mechanisms remain unclear and warrant further investigation. Recent studies have provided more in-depth insights into the complex interplay between COVID-19 and thyroid function. For instance, a study by Smith et al [21] identified COVID-19-related thyroid dysfunction, including subacute thyroiditis and hyperthyroidism, reporting cases of patients experiencing thyroid-related symptoms during or following COVID-19 infection. Similarly, Damara et al [10] conducted a systematic review and meta-analysis, revealing a significant association between autoimmune thyroid diseases and the severity of COVID-19. These studies underscore the importance of further understanding the relationship between COVID-19 and thyroid dysfunction. Additionally, Muller et al [26] examined the underlying mechanisms of COVID-19-induced thyroid dysfunction, particularly focusing on the immune response’s role in thyroid autoimmunity. Their findings suggest that the cytokine storm triggered by COVID-19 may play a crucial role in the development of thyroid diseases. Liu et al [27] investigated the impact of SARS-CoV-2 infection on the expression of thyroid-related genes in thyroid tissue, shedding light on the potential molecular pathways involved. To broaden the context, we have also incorporated recent research on COVID-19 vaccine immunogenicity in patients with autoimmune diseases, providing additional understanding of how immune responses to COVID-19 vaccination may differ in individuals with pre-existing autoimmune conditions [28].

Furthermore, recent investigations have explored the complex interplay between GD and other thyroid-related conditions in the context of COVID-19. For example, Nakano et al [29] found that individuals with GD may be at an increased risk of contracting COVID-19 and could face more severe outcomes postinfection, including complications such as thyrotoxicosis. This study highlights the bidirectional relationship between GD and COVID-19, emphasizing the importance of comprehensive research to better understand the complex interactions between thyroid-related conditions and COVID-19. In a study by Sethi et al [30], researchers observed that COVID-19 infection was associated with thyroid abnormalities, with some patients developing thyrotoxicosis. This suggests that COVID-19 may influence thyroid function, raising concerns about potential implications for individuals with GD. Additionally, Croce et al [31] examined the bidirectional effects of GD and COVID-19, proposing mechanisms through which GD could increase susceptibility to COVID-19 and worsen clinical outcomes, such as immune system dysregulation and cytokine imbalances. However, both COVID-19 and GD can significantly impact physical and mental health, and thus, we have integrated insights from recent research on physical activity and mental health interventions, which may provide potential strategies for improving long-term patient outcomes [32]. Collectively, these studies underscore the urgent need for further research into the multifaceted interactions between COVID-19 and thyroid-related diseases, including GD. This will not only deepen our understanding of the pathogenesis of these conditions but also offer critical insights for health care practitioners, aiding in the development of more informed and effective clinical strategies.

It is important to note that despite the strengths of the MR approach, our study has several limitations. MR methods rely on certain assumptions, including the absence of horizontal pleiotropy. Although we used various strategies to address potential pleiotropic effects, we cannot entirely exclude the possibility of unmeasured confounders influencing our results. Furthermore, our analysis primarily relied on data from the European population, which may limit the generalizability of our findings to other ethnic groups. Specifically, the wide CIs for COVID-19 susceptibility suggest that the study may be underpowered to detect modest effects. Additionally, the definition of COVID-19 cases included self-reported cases, which could introduce reporting bias. The combination of laboratory-confirmed, electronic health record–derived, and self-reported cases may also affect the reliability of exposure classification. However, sensitivity analyses on subsets of laboratory-confirmed and electronic health record–derived cases support the robustness of our findings. Similarly, the definition of GD cases was restricted to hospitalized patients, which could result in selection bias, underrepresenting mild or moderate cases. While hospitalization-based diagnoses enhance diagnostic accuracy, future research should incorporate outpatient and primary care datasets to capture the full spectrum of disease severity. Lastly, this study did not fully explore the potential bidirectional relationships or temporal dynamics between COVID-19 and GD. Future studies should address these aspects using bidirectional MR and longitudinal cohort studies to further clarify the interactions between these conditions.

In summary, our MR analysis did not identify significant causal relationships between COVID-19 susceptibility, COVID-19 hospitalization, or COVID-19 severity and the risk of developing GD. These findings highlight the complex interactions between viral infections, autoimmune diseases, and genetic factors. However, they also emphasize the need for further investigation into the bidirectional relationships and temporal dynamics between COVID-19 and thyroid-related conditions. Expanding this research will deepen our understanding of the pathogenesis of both diseases, contributing valuable insights for clinical decision-making and management strategies.