Mendelian Randomization Reveals Causal Links Between Vertigo Types and structural characteristics of specific brain regions

doi:10.21203/rs.3.rs-4963996/v1

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Mendelian Randomization Reveals Causal Links Between Vertigo Types and structural characteristics of specific brain regions

https://doi.org/10.21203/rs.3.rs-4963996/v1

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Background

Vertigo is a common clinical symptom that involves multiple neurobiological processes; however, its exact mechanism remains elusive. In neuroimaging studies focusing on vertigo and its central correlation, potential reverse causality and unmeasured confounding factors frequently introduce biases. Furthermore, the causal relationship between vertigo and specific neuroimaging features is not yet established. Employing the Mendelian randomization (MR) method can provide a more precise understanding of the causal relationships between vertigo and changes in brain structure and function.

Methods

Based on the large-scale genome-wide association study data from UK Biobank, this study employed bidirectional MR analysis to explore the causal relationships between brain MRI features associated with vertigo and the condition itself. The research focuses on brain imaging-derived phenotypes (IDPs) such as whole brain volume, and the volumes of both gray matter and white matter.

Results

In this study, MR analysis revealed that for benign paroxysmal positional vertigo (BPV), an increase in specific brain regions such as BA-exvivo lh volume BA2, aparc-Desikan rh area rostralmiddlefrontal, IDP dMRI TBSS L2 Corticospinal tract R, and rfMRI connectivity (ICA100 edge 1323) was significantly correlated with a reduction in BPV risk. Conversely, an increase in IDP dMRI TBSS MD Cingulum hippocampus L and rfMRI connectivity (ICA100 edge 82 and 357) was associated with an increased risk of BPV. For peripheral vertigo (PERIPHVERTIGO), an increase in aparc-a2009s rh volume Pole-occipital significantly increased the risk. For general vertigo (VERTIGO), increases in IDP dMRI TBSS FA Superior fronto-occipital fasciculus R and rfMRI connectivity (ICA100 edge 236) were associated with increased risk, while a decrease in rfMRI connectivity (ICA100 edge 184) was associated with decreased risk. For central vertigo (VERTIGOCENT), an increase in rfMRI connectivity (ICA100 edge 1387) and BA-exvivo rh thickness BA4a significantly reduced the risk, whereas an increase in aparc-Desikan rh area annularcingulate significantly increased the risk.

Conclusion

The genetic susceptibility of the vertigo network, extending from the vestibular labyrinth in the cerebellum and brainstem to the cerebral cortex, is causally related to an increase in white matter volume and total brain volume. Volume changes in several cortical regions may suggest a higher risk of vertigo; thus, further studies of causal inference at the sub-brain regional level are strongly recommended. Our results offer genetic evidence that helps elucidate the underlying pathophysiological mechanisms of neuroanatomical abnormalities related to vertigo.

Vertigo

Brain Structure and Function

Benign Paroxysmal positional Vertigo

Mendelian randomization

Spatial Orientation and Posture Control

This study revealed the causal relationship between brain structure and functional characteristics and vertigo through Mendelian randomization (MR) analysis. The analysis showed that changes in volume and functional connectivity in specific brain regions significantly influence the risk of various types of vertigo, including benign paroxysmal positional vertigo (BPV), peripheral vertigo (PERIPHVERTIGO), general vertigo (VERTIGO), and VERTIGOCENT (VERTIGOCENT). These findings highlight potential biomarkers and intervention targets for the prevention and treatment of vertigo, and enhance our understanding of the neurobiological basis of vertigo. Future studies should validate these results in a broader population and delve deeper into potential mechanisms and biomarkers.

Vertigo is one of the most common symptoms in emergency, otorhinolaryngology, and neurology, often manifested as motor or positional hallucinations that reflect the body's challenges in spatial positioning and gravity perception. Vertigo can occur at all ages, with a prevalence of about 5% and an annual incidence of 1.4%, and may be closely related to various brain diseases ^[1][2]. Advancements in neuroimaging have demonstrated that the network involved in vertigo extends from the vestibular labyrinth of the cerebellum and brainstem to the cerebral cortex^[3][4].Although existing clinical studies have identified multiple potential neuropathological mechanisms, they are often limited by small sample sizes, the inability to rule out unknown confounding factors, and challenges in establishing causality. MR, a method that employs genetic variants to elucidate causal dynamics between exposures and outcomes, effectively bypasses these limitations^[5]. This approach posits that genetic variants pertinent to exposures are allocated randomly at conception, thus mitigating the influence of reverse causation and prevalent confounding variables such as educational level, psychological conditions, blood pressure, and lifestyle factors. In this investigation, a bilateral MR framework was applied for the first time to rigorously delineate the causal associations between vertigo and neuroanatomical alterations from a genetic viewpoint.

This MR analysis utilizes summary statistics derived from existing genome-wide association study (GWAS) datasets. Ethical approvals and informed consents were secured during the initial data collection, thereby eliminating the need for additional ethical clearance for this analysis.

2.1 Experimental Design

In our research, the causal relationship between MRI findings and vertigo was explored through two-sample MR analysis. MR employs genetic variants as instrumental variables (IVs) to deduce causality. We used single nucleotide polymorphisms (SNPs) as proxies for exposure, adhering to three pivotal assumptions: (1) Genetic variation is directly correlated with the environmental exposure; (2) it should be unrelated to any potential confounding factors affecting the results; (3) and must influence the results only through the exposure pathway. This analytical framework has unveiled the causal relationship between MRI findings and vertigo diseases, thus providing a foundation for developing prevention and treatment strategies. The process flow of this research is depicted in Fig. 1.

2.2 Data Source

MRI data for this research were sourced from a comprehensive GWAS conducted by UK Biobank. This dataset includes multimodal brain MRI data of approximately 40,000 participants, featuring various modalities such as T1-weighted, T2-weighted-FLAIR, susceptibility-weighted, diffusion, task-functional, and resting-state MRI. Studies focused on brain imaging-derived phenotypes (IDPs) like whole-brain volume, gray matter, and white matter volumes, assessing volume, density, and functional connectivity across frontal, parietal, occipital, and temporal lobes. Vertigo data were sourced from the FinnGen database, covering 4,617 cases and 152,226 controls (identifiers: finngen_R10_H8_BPV, finn-b-H8_PERIPHVERTIGO, finn-b-H8_VERTIGO, finn-b-H8_VERTIGOCENT). All datasets were acquired from the IEU Open GWAS project (https://gwas.mrcieu.ac.uk/).

2.3 Instrumental Variable Selection

In this analysis, we identified significant single nucleotide polymorphisms (SNPs) employing a genome-wide significance threshold (P < 5 × 10^-8) for screening potential instrumental variables (IVs). We applied the 'TwoSampleMR' software package to establish thresholds for SNPs in linkage disequilibrium (LD) (R^2 < 0.01), and restricted our analysis to SNPs within 1,000 base pairs (kb) to mitigate the influence of LD. Additionally, we documented the relevant information for each SNP,, including chromosome location, effect allele (EA), alternate allele (OA), effect allele frequency (EAF), effect size (β), standard error (SE), and P-value, to aid in calculating F-statistics and curtailing potential weak instrument bias. An F-value exceeding 10 is mandated before advancing with further MR analysis^[6]. These steps ensure that the instrumental variables used are statistically robust and provide a solid foundation for subsequent MR analysis.

3.1 Basic Analysis

To estimate the causal effect of MRI on vertigo, we performed a two-sample MR (MR) analysis, as outlined in Step 1A and Step 2A of Fig. 1. The analysis was conducted using the inverse variance weighting (IVW) method as the main analysis tool. A Wald ratio test was performed on features containing a single instrumental variable. MR results were expressed as odds ratios (OR) with 95% confidence intervals (CI). When the P-value of the IVW is less than 0.001 and is consistent with the direction of MR-Egger, Weighted Median Estimator (WME), and the Simple Mode, the findings are deemed statistically significant.

3.2 Two-Way Causality Analysis

To evaluate the bidirectional causal effect between MRI characteristics and vertigo diseases (BPV, PERIPHVERTIGO, VERTIGO, VERTIGOCENT), we classified vertigo diseases as 'exposure' data and screened for factors associated with vertigo as 'outcomes' (Fig. 1). We selected SNPs (P < 5 × 10^-8) significantly associated with vertigo as instrumental variables (IVs) for reverse MR analysis. This approach ensures that the results from the reverse MR analysis do not indicate adverse effects of vertigo on MRI characteristics, thus confirming the directionality and reliability of our research findings.

3.3 Cochran Q Test and Sensitivity Analysis

The Cochran Q test was used to evaluate the heterogeneity among the selected SNPs. When the P value was lower than 0.05, significant heterogeneity was indicated. Through the visual inspection of the scatter plot and funnel plot, we further confirmed the robustness and consistency of the analysis results. Additionally, we utilized five MR methods (IVW, MR Egger, WME, Simple Mode, WM) with different pleiotropic assumptions to generate effect estimates for sensitivity analysis. The IVW method, used as the main analysis tool, provides accurate effect estimation by synthesizing the Wald ratios of all selected effective SNPs. MR-Egger analysis evaluates the potential impact of lateral pleiotropy, and its intercept term's non-significance enhances the credibility of our causal inference. The MR-PRESSO method identifies and corrects heterogeneity and potential outliers, thus reinforcing the robustness of the analysis. All MR analyses were performed using R software (version 4.3.0).

4.1Instrumental variable selection Instrumental variable selection

At the P < 5 × 10^-8 level, we identified 14 MRI-related SNPs associated with a total of 416 significant genetic associations (see additional file1 : Table S1). The F-statistics for all SNPs used in the analysis were greater than 10.

4.2 Sensitivity analysis

To evaluate the robustness of our MR analysis, we first used the intercept method of MR-Egger regression to assess the effect of genetic pleiotropy. The results indicated that genetic pleiotropy did not bias the analysis (P > 0.05). Additionally, the MR-PRESSO analysis was applied to detect and correct potential pleiotropy at the level, and the results confirmed no significant level pleiotropy in our study (P > 0.05). Cochran's Q test showed no significant heterogeneity among the selected SNPs (P > 0.05). (See additional file2 Table S2)

We also performed a 'leave-one-out' analysis, which confirmed the reliability of the MR analysis. The results showed that excluding any single SNP had little effect on the overall results, indicating the robustness of the original causal effect (see additional file3: Figures S1). Scatter plots, funnelplot and forest plots illustrated the overall effect of MRI on vertigo and confirmed the causal relationship between the exposure factor (MRI) and the outcome (vertigo diseases) (see additional file1: Figures S2-4), thereby substantiating the robustness of the analysis results.

4.3 MRI and Vertigo

In our MR analysis, we evaluated the relationship between multiple MRI exposure factors and various vertigo diseases. For BPV, significant reductions in risk were associated with several factors: BA-exvivo lh volume BA2 (OR = 0.8406, 95% CI = 0.7594–0.9305, P = 0.0008), aparc-Desikan rh area rostral middle frontal (OR = 0.8219, 95% CI = 0.7354–0.9186, P = 0.0005), IDP dMRI TBSS L2 Corticospinal tract R (OR = 0.8407, 95% CI = 0.7586–0.9317, P = 0.0009), and rfMRI connectivity (ICA100 edge 1323) (OR = 0.7859, 95% CI = 0.6917–0.8931, P = 0.0002). Conversely, increased risks were noted for IDP dMRI TBSS MD Cingulum hippocampus L (OR = 1.1290, 95% CI = 1.0512–1.2127, P = 0.0009), and rfMRI connectivity (ICA100 edges 82 and 357) with ORs of 1.4971 (95% CI = 1.2419–1.8047, P = 2.32E-05) and 1.2158 (95% CI = 1.0823–1.3658, P = 0.0009), respectively.

For peripheral vertigo, increased risk was linked to aparc-a2009s rh volume Pole-occipital (OR = 1.3316, 95% CI = 1.1315–1.5670, P = 0.0006). In the case of general vertigo the factors increasing risk included IDP dMRI TBSS FA Superior fronto-occipital fasciculus R (OR = 1.1563, 95% CI = 1.0684–1.2513, P = 0.0003) and rfMRI connectivity (ICA100 edge 236) (OR = 1.3246, 95% CI = 1.1397–1.5396, P = 0.0002), while rfMRI connectivity (ICA100 edge 184) significantly reduced the risk (OR = 0.8445, 95% CI = 0.7637–0.9339, P = 0.0010).

For VERTIGOCENT, significant reductions in risk were noted for rfMRI connectivity (ICA100 edge 1387) (OR = 0.2933, 95% CI = 0.1425–0.6035, P = 0.0009) and BA-exvivo rh thickness BA4a (OR = 0.4136, 95% CI = 0.2605–0.6569, P = 0.0002). However, an increased risk was associated with aparc-Desikan rh area circumcisingulate (OR = 2.4559, 95% CI = 1.4476–4.1668, P = 0.0009). A selection of these results is shown in Fig. 2, (See additional file4 Table S3)

4.5 Reverse MR Analysis

For BPV, PERIPHVERTIGO, vertigo, and vertigocent, reverse causality to the neuroimaging features examined was not evident. The odds ratios for all factors were approximately 1, with 95% confidence intervals crossing 1, and P-values exceeding 0.05, indicating no significant reverse causal relationships.

Vertigo is typically categorized into peripheral and central types. In clinical practice, MRI is pivotal for diagnosing suspected VERTIGOCENT to exclude other potential pathologies^[7]. Although the imaging diagnosis of PERIPHVERTIGO, such as BPV remains controversial^{[8, 9]}, it is generally accepted that PERIPHVERTIGO arises from dysfunction within the vestibular terminal organ or the vestibular portion of the eighth cranial nerve in the labyrinth^[10].However, advancements in MRI technology and more comprehensive imaging studies have revealed that vertigo is not solely linked to vestibular system dysfunction. It also involves the primary vestibular cortex, such as the parieto-insular vestibular cortex (PIC) and the occipital pole 2 (OP2), as well as the somatosensory cortex, higher visual areas (such as visual area 5/central temporal area), the cingulate sulcus visual area, and the thalamus vertigo network ^{[11, 12]}. In our study, we employed a bidirectional MR analysis to systematically explore the causal relationships between 3,935 structural and functional imaging-derived phenotypes (IDPs), such as gray matter volume (GMV), cortical properties, and functional connectivity, and various vertigo diseases.

The complexity of human spatial orientation and posture control is achieved through the effective central integration of the vestibular system with proprioception, visual, and auditory cues^[13]. Specifically, vestibular signals are transmitted to the vestibular cortex via vestibular nerves, vestibular nuclei, the brainstem, and the thalamus^[14]. Brandt et al.demonstrated that in cases of impaired central vestibular function, such as BPPV, the vestibular cortex and related subcortical regions enhance functional activities through central compensation to manage persistent vestibular stimulation^[15]. This compensatory function of the central nervous system may persist even after the reduction of otolith particles^[16].

The occipital lobe, pivotal in processing visual information, contains the primary visual cortices V1 and V2, along with the central temporal gyrus dedicated to visual motion. This specialization is crucial for integrating visual and vestibular data.^[17]。Research has shown a marked decrease in neural activity in areas including the inferior frontal gyrus, left hippocampus, anterior cingulate cortex, and both the posterior and anterior insula among patients suffering from chronic subjective vertigo (CSD).Concurrently, there is a significant decrease in functional connectivity between these areas, the intraparietal sulcus-vestibular cortex (PIVC), and the occipital lobe's visual cortex, which likely hinders the processing of visual and vestibular signals and forces a greater reliance on visual cues for spatial orientation^[18]. Additionally, connectivity disruptions between the anterior insula and the occipital cortex in CSD patients point to impaired visual-vestibular interactions, further deteriorating spatial orientation capabilities^[18].Our analysis indicates that an increase in the volume of the occipital pole-occipital region, as measured by aparc-a2009s rh, is linked to an increased risk of peripheral vertigo. This may stem from a disrupted process of fusing visual and vestibular information. Given its role as the core of visual processing, an enlargement of the occipital lobe volume suggests a significant disruption in this essential integration process, thus heightening the risk of peripheral vertigo.

The hippocampus plays a crucial role in processing vestibular inputs for spatial localization ^[14]. Decreased hippocampal function in patients with chronic subjective dizziness may diminish their ability to contextualize spatial motion stimuli within an appropriate environmental setting. Additionally, diminished activity in the anterior insula and anterior cingulate cortex compromises their capacity to evaluate the relevance of such information^[18]. Moreover, vertigo, characterized as an unpleasant and subjective experience, involves the hippocampus significantly in the contextual adjustment of memory ^[19]. In anxiety disorders, the left parahippocampal gyrus operates in concert with the hippocampus and the anterior cingulate cortex/medial prefrontal cortex; these areas are activated during the processing of pathogenic anxiety^[20]. Our analysis indicates that an increase in IDP dMRI TBSS MD Cingulum hippocampus L is associated with an elevated risk of BPV, likely due to alterations or degradation of white matter microstructure, which affects the transmission of information between the hippocampus and other critical brain regions, such as the anterior cingulate cortex and anterior insula.

For example, the prefrontal area, closely related to spatial cognition and self-perception^[21], was found in our analysis to be associated with a reduced risk of BPV when increased in volume, such as the BA-exvivo lh volume BA2 and the aparc-Desikan rh area rostral middle frontal. This increase in volume may reflect adaptive or compensatory changes in the nervous system in response to abnormal vestibular signal processing, potentially stabilizing vestibular input and thereby reducing the incidence of vertigo.In contrast, an increase in the aparc-a2009s rh volume Pole-occipital in the occipital region was associated with an increased risk of PERIPHVERTIGO. The occipital lobe, a center for visual processing, may exhibit increased volume due to disorders in the fusion process of visual and vestibular information, thereby elevating the risk of PERIPHVERTIGO.

The direct connection between the cerebellum and the vestibular nucleus is crucial for maintaining body balance and spatial positioning^[4]. Research suggests a network involving the cortex, basal ganglia, cerebellum, and thalamus is essential for understanding the neural basis of vertigo^[11]. The synergy between the cerebellum and basal ganglia plays a pivotal role in regulating target-related behavioral and emotional responses. This functional collaboration allows the brain to select appropriate cortical responses, inhibit inappropriate reactions, and adjust behavioral strategies based on environmental demands^[22]. Qian Zhu observed significantly enhanced functional activities in specific regions of the pons and cerebellum in BPPV patients^[23]. This finding aligns with our two-way MR analysis, which indicated that a reduction in specific functional connectivity, such as rfMRI connectivity (ICA100 edges 1323, 184, 1387), is associated with reduced BPV risk. These changes suggest that modifications in the cerebellum and its connections are crucial for normal vestibular function regulation, potentially involving inhibition or enhancement of network activities related to vestibular information processing. Moreover, studies have also indicated that compared to healthy controls, BPV patients exhibit significantly reduced functional connectivity between the left OP2 and the left angular gyrus, thalamus, precuneus parietal lobe, central prefrontal gyrus, and right cerebellum posterior lobe^[24].. These declines in connectivity, consistent with our rfMRI data (ICA100 edges 357, 82, 236), underscore the cerebellum’s critical role in vestibular stability and input processing, pointing to these abnormal network connections as potential early biomarkers for vertigo-related brain dysfunction.Ultimately, the reverse MR analysis in our study did not reveal a significant causal effect of brain structure on vertigo, suggesting that while structural brain changes correlate with vertigo, they may not directly cause it.

In this MR study, we employed a variety of evaluation methods to assess the results of the two-way MR analysis, effectively mitigating heterogeneity and pleiotropy. We first screened potential instrumental variables to reduce the interference of potential confounding factors, thus enhancing the robustness of our causal assessments compared to traditional observational studies^[25]. We highlighted the complex interactions between vertigo and specific neuroimaging indicators, providing new insights for future diagnostic and therapeutic strategies. Further, we enhanced the robustness of our findings through the MR-PRESSO distortion test and sensitivity analysis, ensuring the reliability of our conclusions.However, there are some limitations in our research. First, MRI features are derived from various regions of the brain and are processed using different brain maps and programs, our analysis faces inherent challenges. Moreover, our data on vertigo data originate from European populations, potentially leading to sample overlaps and limitations due to specific genetic backgrounds. Lastly, given the inherent constraints of the MR method, our study requires a larger cohort of observational samples to further validate these findings.

This study utilized two-sample MR analysis, the causal relationship between MRI features and different types of vertigo diseases was confirmed, and the association between structural and functional changes in specific brain regions and vertigo risk was confirmed. Our analysis showed that, for example, increased prefrontal volume ( e.g., BA-exvivo lh volume BA2 and aparc-Desikan rh area rostral middlefrontal ) was significantly associated with decreased risk of BPV. Increased prefrontal volume and functional connectivity changes in the cerebellum. For example, decreased rfMRI connectivity ( ICA100 edge 1323 ) may be associated with a reduced risk of BPV ( BPV ). In addition, the increased volume of other brain regions such as the occipital lobe is associated with an increased risk of PERIPHVERTIGO, highlighting the complex interaction between vertigo symptoms and brain structure and function. These findings not only provide a new perspective for understanding the neural mechanism of vertigo, but also provide potential biomarkers for future diagnosis and treatment strategy development.

Ethics Approval and Consent to Participate

Ethical approvals and informed consents were secured at the time of the original data collection, negating the necessity for further ethical clearance for this analysis.

Consent for Publication

All authors have read and approved the final manuscript and have given their consent for publication.

Competing Interests

The authors declare that they have no commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

This study was supported by funding from the Hunan University of Chinese Medicine School (Z2023JBGS01, CX20230798),.The First Batch of Leading Talents and Academic Leaders Project in Traditional Chinese Medicine in Hunan Province during the 14th Five-Year Plan Period.

Author Contribution

Junwei.Huang: Conceptualization,Data curation,Formal analysis,Writing – original draft. Xiao.Zhu: Formal analysis, Methodology,Validation, Writing – original draft.Jingxin.Yao: Investigation, Supervision, Writing – original draft.Wei.Lu: Software, Visualization,Writing – original draft.Zhenhua.Zhu: Supervision, Validation, Writing – review & editing.

Acknowledgement

The authors affirm that this study they was conducted without any commercial or financial relationships that could be interpreted as potential conflicts of interest.

Availability of data and materials

The data used in this study are derived from publicly available GWAS datasets, which are accessible through the IEU Open GWAS project.

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You are reading this latest preprint version

Mendelian Randomization Reveals Causal Links Between Vertigo Types and structural characteristics of specific brain regions

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

1 Introduction

2. Materials and Methods

2.1 Experimental Design

2.2 Data Source

2.3 Instrumental Variable Selection

3. MR Analysis

3.1 Basic Analysis

3.2 Two-Way Causality Analysis

3.3 Cochran Q Test and Sensitivity Analysis

4. Results

4.1Instrumental variable selection Instrumental variable selection

4.2 Sensitivity analysis

4.3 MRI and Vertigo

4.5 Reverse MR Analysis

5. Discussion

6. Conclusion

Declarations

Competing Interests

Funding

Author Contribution

Acknowledgement

Availability of data and materials

References

Additional Declarations

Supplementary Files

Status:

Version 1