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3D-Neuronavigation In Vivo Through a Patient's Brain During a Spontaneous Migraine Headache
Published on: June 2, 2014
Causal relationships between cortical brain structural alterations and migraine subtypes: a bidirectional Mendelian
Zuhao Sun1, Mengge Liu1, Guoshu Zhao1
1Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China.
Background:
Previous studies have shown that migraines are associated with brain structural changes. However, the causal relationships between these changes and migraine, as well as its subtypes, migraine with aura (MA) and migraine without aura (MO), remain largely unclear.
Methods:
We utilized genome-wide association study (GWAS) summary statistics from European cohorts for 2,347 cortical structural magnetic resonance imaging (MRI) phenotypes, derived from both T1-weighted and diffusion tensor imaging scans (n = 36,663), with migraine and its subtypes (n = 147,970-375,752). Cortical phenotypes included both macrostructural (e.g., cortical thickness, surface area) and microstructural (e.g., fractional anisotropy, mean diffusivity) features. Genetic correlations were first assessed to identify significant associations, followed by bidirectional Mendelian randomization (MR) analyses to determine causal relationships between these brain phenotypes and migraine, as well as its subtypes (MA and MO). Sensitivity analyses were applied to ensure the robustness of the results.
Results:
Genetic correlation analysis identified 510 significant associations between cortical structural phenotypes and migraine across 401 distinct traits. Forward MR analysis revealed nine significant causal effects of cortical structural changes on migraine risk. Specifically, increased cortical thickness and local gyrification index in specific cortical regions were associated with a decreased risk of overall migraine, MA, and MO, while intracellular volume fraction and orientation diffusion index in specific regions increased the risk of MA and MO. Reverse MR analysis demonstrated that MA causally increased mean diffusivity in the insular and frontal opercular cortex. Sensitivity analyses confirmed the robustness of these findings, with no evidence of horizontal pleiotropy or heterogeneity.
Conclusion:
This study identifies causal relationships between cortical neuroimaging phenotypes and migraine, highlighting potential biomarkers for migraine diagnosis, treatment, and prevention.
Insights
Brain structure changes causally impact migraine risk. Specific cortical thickness and gyrification decrease migraine risk, while other microstructural changes increase risk for migraine with aura (MA) and migraine without aura (MO).
Area of Science:
- Neuroimaging
- Genetics
- Neurology
Background:
- Migraine is linked to brain structural changes, but causal links to subtypes like migraine with aura (MA) and migraine without aura (MO) are unclear.
- Understanding these relationships is crucial for developing targeted migraine therapies.
Purpose of the Study:
- To investigate the causal relationships between cortical structural phenotypes and migraine, including its subtypes (MA and MO).
- To identify potential neuroimaging biomarkers for migraine diagnosis and treatment.
Main Methods:
- Utilized genome-wide association study (GWAS) summary statistics for 2,347 cortical MRI phenotypes (macro- and microstructural) and large migraine cohorts.
- Employed genetic correlation and bidirectional Mendelian randomization (MR) analyses to establish causal links.
- Conducted sensitivity analyses to ensure result robustness.
Main Results:
- Identified 510 significant genetic associations between cortical traits and migraine.
- Forward MR revealed nine causal effects: increased cortical thickness and gyrification reduced migraine risk (overall, MA, MO).
- Specific microstructural changes (intracellular volume fraction, orientation diffusion index) increased MA/MO risk; MA causally increased mean diffusivity in specific brain regions.
Conclusions:
- Established causal relationships between specific cortical neuroimaging phenotypes and migraine risk.
- Identified potential neuroimaging biomarkers for migraine diagnosis, treatment, and prevention.
