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Shared Genetic Factors Underlie Migraine and Depression

  • Yuanhao Yang (a1), Huiying Zhao (a1), Andrew C. Heath (a2), Pamela A. F. Madden (a2), Nicholas G. Martin (a3) and Dale R. Nyholt (a1)...


Migraine frequently co-occurs with depression. Using a large sample of Australian twin pairs, we aimed to characterize the extent to which shared genetic factors underlie these two disorders. Migraine was classified using three diagnostic measures, including self-reported migraine, the ID migraine™ screening tool, or migraine without aura (MO) and migraine with aura (MA) based on International Headache Society (IHS) diagnostic criteria. Major depressive disorder (MDD) and minor depressive disorder (MiDD) were classified using the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. Univariate and bivariate twin models, with and without sex-limitation, were constructed to estimate the univariate and bivariate variance components and genetic correlation for migraine and depression. The univariate heritability of broad migraine (self-reported, ID migraine, or IHS MO/MA) and broad depression (MiDD or MDD) was estimated at 56% (95% confidence interval [CI]: 53–60%) and 42% (95% CI: 37–46%), respectively. A significant additive genetic correlation (r G = 0.36, 95% CI: 0.29–0.43) and bivariate heritability (h 2 = 5.5%, 95% CI: 3.6–7.8%) was observed between broad migraine and depression using the bivariate Cholesky model. Notably, both the bivariate h 2 (13.3%, 95% CI: 7.0–24.5%) and r G (0.51, 95% CI: 0.37–0.69) estimates significantly increased when analyzing the more narrow clinically accepted diagnoses of IHS MO/MA and MDD. Our results indicate that for both broad and narrow definitions, the observed comorbidity between migraine and depression can be explained almost entirely by shared underlying genetically determined disease mechanisms.

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Corresponding author

Address for correspondence: Yuanhao Yang and Dale R. Nyholt, Statistical and Genomic Epidemiology Laboratory, Institute of Health and Biomedical Innovation, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia. E-mail: and


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