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Structural brain age gap and clinical determinants in migraine: a cross-sectional MRI study
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DOI：10.1186/s10194-026-02480-2.png)
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Abstract
En 中文
Migraine has been linked to structural brain alterations that may deviate from normative aging patterns. Recent brain-age modeling studies have reported elevated brain age gap (BAG) values in migraine populations, but the clinical factors associated with individual variation in BAG remain incompletely characterized. This study quantified BAG in patients with migraine and identified demographic, lifestyle, and clinical factors independently associated with structural brain-age deviation. This cross-sectional study enrolled 128 patients with migraine (ICHD-3 criteria) and 35 non-migraine controls. Brain age was estimated using a support vector regression model trained on T1-weighted MRI scans from an independent multicenter dataset of 1,410 healthy adults. The primary outcome was the bias-corrected BAG. Multivariable linear regression analysis identified independent predictors of BAG within the migraine cohort across headache, psychiatric, sleep, and lifestyle domains. An exploratory extreme-group comparison contrasted migraine patients in the upper and lower BAG tertiles using binary logistic regression. Patients with migraine exhibited a significantly higher bias-corrected BAG than controls (9.76 ± 8.97 vs. 4.88 ± 8.25 years; ANCOVA adjusted for age, age², and total intracranial volume: F = 6.795, p = 0.010, partial η²=0.041). In multivariable linear regression analysis, depressive symptom severity (Beck Depression Inventory-II [BDI-II]: β = 0.39, 95% CI = 0.03–0.75, p = 0.033) was independently associated with a larger BAG. Current smoking was also independently associated with a larger BAG (β = 7.56, 95% CI = 0.63–14.48, p = 0.033), although this estimate was based on only 10 current smokers and should be interpreted with caution. In the exploratory extreme-group analysis, higher depressive symptoms (BDI-II, OR = 1.24, 95% CI = 1.04–1.49, p = 0.019) were associated with the high-aging phenotype. Headache frequency, disease duration, and aura status showed no significant association with BAG in any analysis. Migraine was associated with a significantly higher structural BAG relative to non-migraine controls. Within the migraine cohort, depressive symptom burden was the most consistent clinical correlate of BAG, whereas current smoking emerged as a preliminary lifestyle signal requiring confirmation in cohorts with more current smokers. These findings suggest that structural brain-age deviation in migraine is associated with psychiatric and lifestyle factors beyond headache-specific characteristics, supporting further longitudinal research into potentially modifiable clinical correlates.
Keywords:
Brain age gap
Migraine
Gray matter volume
Machine learning
Depression
Smoking
Sex differences
Support vector regression
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