Review Article | Published:

Migrainomics — identifying brain and genetic markers of migraine

Nature Reviews Neurology volume 13, pages 725741 (2017) | Download Citation

Abstract

Migraine is one of the world's most prevalent and disabling disorders and imposes an enormous socioeconomic burden. The exact causes of migraine are unknown, and no recognizable diagnostic pathological changes have been identified. Specific identifiable markers of migraine would aid diagnosis and could provide insight into the pathogenesis of the condition, with the potential to direct development of new therapeutics. In the past few years, advances in neuroimaging and genetic studies have provided the most substantial progress towards the identification of markers. A growing number of brain imaging studies have provided important insights into the brain mechanisms that underlie migraine symptoms during and between migraine attacks. Similarly, large-scale genome-wide association studies have identified genetic variants associated with the common forms of migraine — migraine with aura and migraine without aura. In total, 44 independent single-nucleotide polymorphism loci have been robustly associated with the risk of migraine and provide new evidence for the involvement of vascular mechanisms. Both imaging and genetics, therefore, have excellent potential as markers of migraine. In this Review, we provide a summary of results regarding current and potential neuroimaging and genetic markers of migraine, consider what conclusions can be drawn from these markers about migraine mechanisms and discuss the potential of combining imaging and genetics.

Key points

  • Advances in neuroimaging and genetic studies have enabled substantial progress to be made towards the identification of migraine biomarkers

  • Brain function, structure and chemistry are altered in migraineurs versus healthy controls

  • Brain metrics such as functional MRI or voxel-based morphometry can be used as biomarkers of the disease state and treatment effects

  • Genetic findings have provided new evidence for the involvement of vascular mechanisms in migraine

  • Brain systems are also dependent on genetic determinants

  • A combination of genetic and imaging markers of migraine will deepen our understanding of migraine aetiology and improve our ability to prevent and treat attacks

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References

  1. 1.

    GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 388, 1545–1602 (2016).

  2. 2.

    et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380, 2163–2196 (2012).

  3. 3.

    et al. The cost of headache disorders in Europe: the Eurolight project. Eur. J. Neurol. 19, 703–711 (2012).

  4. 4.

    , & The prevalence and characteristics of migraine in a population-based cohort: the GEM study. Neurology 53, 537–542 (1999).

  5. 5.

    , , & Handbook of headache management: a practical guide to diagnosis and treatment of head, neck, and facial pain 1st edn (Williams & Wilkins, 1993).

  6. 6.

    , , , & The inheritance of migraine with aura estimated by means of structural equation modelling. J. Med. Genet. 36, 225–227 (1999).

  7. 7.

    , , , & The relative role of genetic and environmental factors in migraine without aura. Neurology 53, 995–999 (1999).

  8. 8.

    et al. Genetic and environmental influences on migraine: a twin study across six countries. Twin Res. 6, 422–431 (2003).

  9. 9.

    et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat. Genet. 47, 702–709 (2015).

  10. 10.

    & Genome-wide association studies in migraine: current state and route to follow. Curr. Opin. Neurol. 29, 302–308 (2016). A review of genetic association studies of migraine. Importantly, this review discusses the various strategies being tested to identify which pathophysiological mechanisms are involved, how they can be studied and what this means for clinical diagnosis and patient care.

  11. 11.

    & Biomarkers associated with migraine and their potential role in migraine management. Headache 53, 1262–1277 (2013).

  12. 12.

    et al. Visual evoked potentials in subgroups of migraine with aura patients. J. Headache Pain 16, 92 (2015).

  13. 13.

    , & Headache frontiers: using magnetoencephalography to investigate pathophysiology of chronic migraine. Curr. Pain Headache Rep. 17, 309 (2013).

  14. 14.

    et al. Three-dimensional localization of abnormal EEG activity in migraine: a low resolution electromagnetic tomography (LORETA) study of migraine patients in the pain-free interval. Brain Topogr 21, 36–42 (2008).

  15. 15.

    Headache Classification Committee of the International Headache Society. The international classification of headache disorders: 3rd edition (beta version). Cephalalgia 33, 629–808 (2013).

  16. 16.

    et al. Sex and the migraine brain. Neurobiol. Dis. 68, 200–214 (2014).

  17. 17.

    et al. Brain changes in responders versus non-responders in chronic migraine: markers of disease reversal. Front. Hum. Neurosci. 10, 497 (2016).

  18. 18.

    et al. The migraine brain in transition: girls versus boys. Pain 156, 2212–2221 (2015). This paper was the first to look at sex differences in paediatric migraineurs during the important developmental transition between ages 10–16 years, and to examine the increases in migraine prevalence in women during and following puberty.

  19. 19.

    et al. In medication-overuse headache, fMRI shows long-lasting dysfunction in midbrain areas. Headache 52, 1520–1534 (2012).

  20. 20.

    , , & Functional reorganization of the default mode network across chronic pain conditions. PLoS ONE 9, e106133 (2014).

  21. 21.

    , & Use of functional imaging across clinical phases in CNS drug development. Transl Psychiatry 3, e282 (2013).

  22. 22.

    , & Biomarkers for chronic pain and analgesia. Part 1: the need, reality, challenges, and solutions. Discov. Med. 11, 197–207 (2011).

  23. 23.

    , & Biomarkers for chronic pain and analgesia. Part 2: how, where, and what to look for using functional imaging. Discov. Med. 11, 209–219 (2011).

  24. 24.

    , , , & The premonitory phase of migraine — what can we learn from it? Headache 55, 609–620 (2015).

  25. 25.

    & The migraine generator revisited: continuous scanning of the migraine cycle over 30 days and three spontaneous attacks. Brain 139, 1987–1993 (2016). A paper that used functional MRI to capture the migraine cycle over time and thus characterize all phases of the migraine phenotype — additional studies similar to this one are needed.

  26. 26.

    , & Hypothalamus as a mediator of chronic migraine: evidence from high-resolution fMRI. Neurology 88, 2011–2016 (2017).

  27. 27.

    et al. Neural mechanism for hypothalamic-mediated autonomic responses to light during migraine. Proc. Natl Acad. Sci. USA 114, E5683–E5692 (2017).

  28. 28.

    Migraine and the hypothalamus. Cephalalgia 29, 809–817 (2009).

  29. 29.

    et al. Autonomic impairment in patients with migraine. Eur. Rev. Med. Pharmacol. Sci. 19, 3922–3927 (2015).

  30. 30.

    , , , & Hypothalamic activation in spontaneous migraine attacks. Headache 47, 1418–1426 (2007). One of the first studies to demonstrate the importance of the hypothalamus, a key autonomic region, in migraine.

  31. 31.

    , , , & Brain activations in the premonitory phase of nitroglycerin-triggered migraine attacks. Brain 137, 232–241 (2014).

  32. 32.

    , , & Photic hypersensitivity in the premonitory phase of migraine — a positron emission tomography study. Eur. J. Neurol. 21, 1178–1183 (2014).

  33. 33.

    et al. Mechanisms of migraine aura revealed by functional MRI in human visual cortex. Proc. Natl Acad. Sci. USA 98, 4687–4692 (2001).

  34. 34.

    et al. Clinical relevance of cortical spreading depression in neurological disorders: migraine, malignant stroke, subarachnoid and intracranial hemorrhage, and traumatic brain injury. J. Cereb. Blood Flow Metab. 31, 17–35 (2011).

  35. 35.

    et al. Activation of meningeal nociceptors by cortical spreading depression: implications for migraine with aura. J. Neurosci. 30, 8807–8814 (2010).

  36. 36.

    et al. The thalamic reticular nucleus is activated by cortical spreading depression in freely moving rats: prevention by acute valproate administration. Eur. J. Neurosci. 41, 120–128 (2015).

  37. 37.

    et al. Cortical spreading depression as a target for anti-migraine agents. J. Headache Pain 14, 62 (2013).

  38. 38.

    et al. Triptans disrupt brain networks and promote stress-induced CSD-like responses in cortical and subcortical areas. J. Neurophysiol. 115, 208–217 (2016).

  39. 39.

    et al. Interhemispheric differences of fMRI responses to visual stimuli in patients with side-fixed migraine aura. Hum. Brain Mapp. 35, 2714–2723 (2014).

  40. 40.

    , , , & Interictal cortical hyperresponsiveness in migraine is directly related to the presence of aura. Cephalalgia 33, 365–374 (2013).

  41. 41.

    , , & Specific and somatotopic functional magnetic resonance imaging activation in the trigeminal ganglion by brush and noxious heat. J. Neurosci. 23, 7897–7903 (2003).

  42. 42.

    , , & Trigeminal nociceptive transmission in migraineurs predicts migraine attacks. J. Neurosci. 31, 1937–1943 (2011).

  43. 43.

    & The enigma of the dorsolateral pons as a migraine generator. Cephalalgia 32, 803–812 (2012).

  44. 44.

    et al. Thalamic sensitization transforms localized pain into widespread allodynia. Ann. Neurol. 68, 81–91 (2010).

  45. 45.

    et al. 3D-neuronavigation in vivo through a patient's brain during a spontaneous migraine headache. J. Vis. Exp. (2014).

  46. 46.

    et al. Painful heat reveals hyperexcitability of the temporal pole in interictal and ictal migraine states. Cereb. Cortex 21, 435–448 (2011).

  47. 47.

    & Increased limbic and brainstem activity during migraine attacks following olfactory stimulation. Neurology 77, 476–482 (2011).

  48. 48.

    et al. Association of μ-opioid activation in the prefrontal cortex with spontaneous migraine attacks — brief report I. Ann. Clin. Transl Neurol. 1, 439–444 (2014).

  49. 49.

    , & Diencephalic and brainstem mechanisms in migraine. Nat. Rev. Neurosci. 12, 570–584 (2011).

  50. 50.

    , , , & Brainstem activation specific to migraine headache. Lancet 357, 1016–1017 (2001).

  51. 51.

    & Investigating the human brainstem with structural and functional MRI. Front. Hum. Neurosci. 8, 116 (2014).

  52. 52.

    & Functional imaging of the human brainstem during somatosensory input and autonomic output. Front. Hum. Neurosci. 7, 569 (2013).

  53. 53.

    , , , & Altered hypothalamic functional connectivity with autonomic circuits and the locus coeruleus in migraine. PLoS ONE 9, e95508 (2014).

  54. 54.

    , & Altered functional magnetic resonance imaging resting-state connectivity in periaqueductal gray networks in migraine. Ann. Neurol. 70, 838–845 (2011). An example of specific circuits involved in brainstem modulation in migraine.

  55. 55.

    , , , & Interictal and postictal cognitive changes in migraine. Cephalalgia 19, 557–565; discussion 541 (1999).

  56. 56.

    et al. Ictal and interictal hypoactivation of the occipital cortex in migraine with aura. A neuroimaging and electrophysiological study. Funct. Neurol. 20, 169–171 (2005).

  57. 57.

    et al. Concurrent functional and structural cortical alterations in migraine. Cephalalgia 32, 607–620 (2012).

  58. 58.

    et al. Chronic migraine with medication overuse pre-post withdrawal of symptomatic medication: clinical results and fMRI correlations. Headache 50, 998–1004 (2010).

  59. 59.

    et al. Her versus his migraine: multiple sex differences in brain function and structure. Brain 135, 2546–2559 (2012). Sex differences in migraine are well defined; this paper reports significant differences between men and women that could contribute to how brain markers of disease need to be dimorphically segregated.

  60. 60.

    & Functional and structural alterations in the migraine cerebellum. J. Cereb. Blood Flow Metab. (2017).

  61. 61.

    et al. Migraine attacks the basal ganglia. Mol. Pain 7, 71 (2011).

  62. 62.

    et al. Structural brain MRI abnormalities in pediatric patients with migraine. J. Neurol. 261, 350–357 (2014).

  63. 63.

    et al. Decrease of gray matter volume in the midbrain is associated with treatment response in medication-overuse headache: possible influence of orbitofrontal cortex. J. Neurosci. 33, 15343–15349 (2013). Migraine is a dynamic state, and biomarker evaluation must take this fact into account; this paper examines migraine responsivity (that is, brain changes) in responders versus non-responders to reversal of medication overuse.

  64. 64.

    , & Losses and gains: chronic pain and altered brain morphology. Expert Rev. Neurother. 13, 1221–1234 (2013).

  65. 65.

    , , , & A meta-analysis of voxel-based morphometric studies on migraine. Int. J. Clin. Exp. Med. 8, 4311–4319 (2015).

  66. 66.

    , & Migraine and structural abnormalities in the brain. Curr. Opin. Neurol. 27, 309–314 (2014).

  67. 67.

    , , , & Migraine is associated with an increased risk of deep white matter lesions, subclinical posterior circulation infarcts and brain iron accumulation: the population-based MRI CAMERA study. Cephalalgia 30, 129–136 (2010).

  68. 68.

    et al. The association between clinical characteristics of migraine and brain GABA levels: an exploratory study. J. Pain 17, 1058–1067 (2016).

  69. 69.

    et al. Elevated levels of GABA+ in migraine detected using 1H-MRS. NMR Biomed. 28, 890–897 (2015). An understanding of the chemical changes in the brains of migraineurs, such as those examined in this study, will become increasingly important, as these alterations present potential biomarkers and targets for therapy development.

  70. 70.

    et al. Grey matter changes associated with medication-overuse headache: correlations with disease related disability and anxiety. World J. Biol. Psychiatry 13, 517–525 (2012).

  71. 71.

    et al. Thickening of the somatosensory cortex in migraine without aura. Cephalalgia 34, 1125–1133 (2014).

  72. 72.

    , , & Thickening in the somatosensory cortex of patients with migraine. Neurology 69, 1990–1995 (2007).

  73. 73.

    , , & Trigeminal somatosensorial evoked potentials suggest increased excitability during interictal period in patients with long disease duration in migraine. Neurosci. Lett. 612, 62–65 (2016).

  74. 74.

    et al. Primary somatosensory cortices contain altered patterns of regional cerebral blood flow in the interictal phase of migraine. PLoS ONE 10, e0137971 (2015).

  75. 75.

    , , , & Abnormal sensorimotor plasticity in migraine without aura patients. Pain 154, 1738–1742 (2013).

  76. 76.

    et al. Altered structure and resting-state functional connectivity of the basal ganglia in migraine patients without aura. J. Pain 14, 836–844 (2013).

  77. 77.

    et al. Atypical resting-state functional connectivity of affective pain regions in chronic migraine. Headache 53, 737–751 (2013). Evaluation of resting states in the brain, as was conducted in this study, could be important for understanding disease state and treatment effects.

  78. 78.

    , , , & The anterior insula shows heightened interictal intrinsic connectivity in migraine without aura. Neurology 84, 1043–1050 (2015).

  79. 79.

    et al. The missing link: enhanced functional connectivity between amygdala and visceroceptive cortex in migraine. Cephalalgia 33, 1264–1268 (2013).

  80. 80.

    et al. Increased functional activation of limbic brain regions during negative emotional processing in migraine. Front. Hum. Neurosci. 10, 366 (2016). This paper was important in demonstrating that brain systems involved in emotional processing are altered in migraineurs, even in the interictal state.

  81. 81.

    et al. The lateral prefrontal cortex mediates the hyperalgesic effects of negative cognitions in chronic pain patients. J. Pain 16, 692–699 (2015).

  82. 82.

    et al. Shape shifting pain: chronification of back pain shifts brain representation from nociceptive to emotional circuits. Brain 136, 2751–2768 (2013).

  83. 83.

    et al. Excitatory neurotransmitters in brain regions in interictal migraine patients. Mol. Pain 5, 34 (2009).

  84. 84.

    et al. Altered neurochemical coupling in the occipital cortex in migraine with visual aura. Cephalalgia 35, 1025–1030 (2015).

  85. 85.

    et al. Dynamic levels of glutamate within the insula are associated with improvements in multiple pain domains in fibromyalgia. Arthritis Rheum. 58, 903–907 (2008).

  86. 86.

    et al. Allodynia and descending pain modulation in migraine: a resting state functional connectivity analysis. Pain Med. 15, 154–165 (2014).

  87. 87.

    et al. Interictal dysfunction of a brainstem descending modulatory center in migraine patients. PLoS ONE 3, e3799 (2008).

  88. 88.

    et al. Altered periaqueductal gray resting state functional connectivity in migraine and the modulation effect of treatment. Sci. Rep. 6, 20298 (2016).

  89. 89.

    , , & Understanding migraine through the lens of maladaptive stress responses: a model disease of allostatic load. Neuron 73, 219–234 (2012). A summary of the complexity of processes that could affect the migraine brain in a dynamic manner, which need to be taken into account in brain biomarker development.

  90. 90.

    et al. Acute migraine medications and evolution from episodic to chronic migraine: a longitudinal population-based study. Headache 48, 1157–1168 (2008).

  91. 91.

    & Concepts and mechanisms of migraine chronification. Headache 48, 7–15 (2008).

  92. 92.

    & Migraine chronification. Curr. Neurol. Neurosci. Rep. 11, 139–148 (2011).

  93. 93.

    & Pathophysiology of migraine chronification. Neurol. Sci. 31, S15–S17 (2010).

  94. 94.

    & Overuse of acute migraine medications and migraine chronification. Curr. Pain Headache Rep. 13, 301–307 (2009).

  95. 95.

    , , & Neuroimaging in chronic migraine. Neurol. Sci. 31, S19–S22 (2010).

  96. 96.

    et al. Functional-MRI evaluation of pain processing in chronic migraine with medication overuse. Neurol. Sci. 30, S71–S74 (2009). Understanding the effects of drugs on the migraine brain is key to the evaluation of biomarkers; the natural history of migraine chronification resulting from medication overuse, as studied in this paper, is a good model with which to achieve this understanding.

  97. 97.

    , , & Brainstem dysfunction in chronic migraine as evidenced by neurophysiological and positron emission tomography studies. Headache 47, 996–1003; discussion 1004–1007 (2007).

  98. 98.

    et al. Gray matter changes related to medication overuse in patients with chronic migraine. Cephalalgia 36, 1324–1333 (2016).

  99. 99.

    & Sex-related differences in migraine. Neurol. Sci. 35 (Suppl. 1), 207–213 (2014).

  100. 100.

    , & Can functional magnetic resonance imaging improve success rates in CNS drug discovery? Expert Opin. Drug Discov. 6, 597–617 (2011).

  101. 101.

    & Triptan-induced disruption of trigemino-cortical connectivity. Neurology 84, 2124–2131 (2015).

  102. 102.

    et al. The insula: a “hub of activity” in migraine. Neuroscientist 22, 632–652 (2015).

  103. 103.

    et al. Familial hemiplegic migraine and episodic ataxia type-2 are caused by mutations in the Ca2+ channel gene CACNL1A4. Cell 87, 543–552 (1996).

  104. 104.

    et al. Haploinsufficiency of ATP1A2 encoding the Na+/K+ pump α2 subunit associated with familial hemiplegic migraine type 2. Nat. Genet. 33, 192–196 (2003).

  105. 105.

    et al. Mutation in the neuronal voltage-gated sodium channel SCN1A in familial hemiplegic migraine. Lancet 366, 371–377 (2005).

  106. 106.

    et al. Familial hemiplegic migraine type 1 mutations W1684R and V1696I alter G protein-mediated regulation of CaV2.1 voltage-gated calcium channels. Biochim. Biophys. Acta 1822, 1238–1246 (2012).

  107. 107.

    et al. A population-based study of familial hemiplegic migraine suggests revised diagnostic criteria. Brain 125, 1379–1391 (2002).

  108. 108.

    et al. A dominant-negative mutation in the TRESK potassium channel is linked to familial migraine with aura. Nat. Med. 16, 1157–1160 (2010).

  109. 109.

    et al. Casein kinase iδ mutations in familial migraine and advanced sleep phase. Sci. Transl. Med. 5, 183ra56 (2013).

  110. 110.

    , , & A comprehensive review of genetic association studies. Genet. Med. 4, 45–61 (2002).

  111. 111.

    et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat. Rev. Neurosci. 14, 365–376 (2013).

  112. 112.

    et al. Systematic re-evaluation of genes from candidate gene association studies in migraine using a large genome-wide association data set. Cephalalgia 36, 604–614 (2016). This comprehensive review of 27 genes from published candidate gene and non-genome-wide association studies in migraine finds no clear evidence for involvement of the previously reported most promising candidate genes in migraine.

  113. 113.

    et al. A high-density association screen of 155 ion transport genes for involvement with common migraine. Hum. Mol. Genet. 17, 3318–3331 (2008).

  114. 114.

    et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet. 9, 356–369 (2008).

  115. 115.

    et al. Genome-wide association study of migraine implicates a common susceptibility variant on 8q22.1. Nat. Genet. 42, 869–873 (2010).

  116. 116.

    et al. Genome-wide association analysis identifies susceptibility loci for migraine without aura. Nat. Genet. 44, 777–782 (2012).

  117. 117.

    et al. Meta-analysis of genome-wide association for migraine in six population-based European cohorts. Eur. J. Hum. Genet. 19, 901–907 (2011).

  118. 118.

    et al. Genome-wide association study reveals three susceptibility loci for common migraine in the general population. Nat. Genet. 43, 695–698 (2011).

  119. 119.

    et al. Genome-wide meta-analysis identifies new susceptibility loci for migraine. Nat. Genet. 45, 912–917 (2013).

  120. 120.

    SECA: SNP effect concordance analysis using genome-wide association summary results. Bioinformatics 30, 2086–2088 (2014).

  121. 121.

    et al. Concordance of genetic risk across migraine subgroups: impact on current and future genetic association studies. Cephalalgia 35, 489–499 (2015). This thorough analysis of genome-wide association results from Ref. 119 shows that the majority of common genetic risk effects are the same across migraine without aura and migraine with aura subgroups, clinic-based and population-based subgroups and male and female patients with migraine subgroups.

  122. 122.

    , , & Five years of GWAS discovery. Am. J. Hum. Genet. 90, 7–24 (2012).

  123. 123.

    et al. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine. Nat. Genet. 48, 856–866 (2016). This is the largest genetic study of migraine to date; the identified loci showed enrichment of genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular aetiologies.

  124. 124.

    et al. Selectivity in genetic association with sub-classified migraine in women. PLoS Genet. 10, e1004366 (2014).

  125. 125.

    1000 Genomes Project Consortium. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).

  126. 126.

    Wellcome Trust Case Control Consortium et al. Bayesian refinement of association signals for 14 loci in 3 common diseases. Nat. Genet. 44, 1294–1301 (2012).

  127. 127.

    et al. Biological interpretation of genome-wide association studies using predicted gene functions. Nat. Commun. 6, 5890 (2015).

  128. 128.

    et al. g:Profiler — a web server for functional interpretation of gene lists (2016 update). Nucleic Acids Res. 44, W83–W89 (2016).

  129. 129.

    et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000).

  130. 130.

    & KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000).

  131. 131.

    , , , & KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, 457–D462 (2016).

  132. 132.

    et al. Annotating cancer variants and anti-cancer therapeutics in reactome. Cancers (Basel) 4, 1180–1211 (2012).

  133. 133.

    et al. The reactome pathway knowledgebase. Nucleic Acids Res. 42, D472–D477 (2014).

  134. 134.

    GTEx Consortium. Human genomics. The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).

  135. 135.

    et al. Shared genetic basis for migraine and ischemic stroke: a genome-wide analysis of common variants. Neurology 84, 2132–2145 (2015).

  136. 136.

    et al. Genetic analysis for a shared biological basis between migraine and coronary artery disease. Neurol. Genet. 1, e10 (2015).

  137. 137.

    et al. Common variation in PHACTR1 is associated with susceptibility to cervical artery dissection. Nat. Genet. 47, 78–83 (2015).

  138. 138.

    Myocardial Infarction Genetics Consortium. et al. Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants. Nat. Genet. 41, 334–341 (2009).

  139. 139.

    et al. Clinical features in a family with an R460H mutation in transforming growth factor β receptor 2 gene. J. Med. Genet. 43, 908–916 (2006).

  140. 140.

    et al. Abdominal aortic aneurysm is associated with a variant in low-density lipoprotein receptor-related protein 1. Am. J. Hum. Genet. 89, 619–627 (2011).

  141. 141.

    et al. Fine mapping of the 1p36 deletion syndrome identifies mutation of PRDM16 as a cause of cardiomyopathy. Am. J. Hum. Genet. 93, 67–77 (2013).

  142. 142.

    et al. Genetics and biomarkers of moyamoya disease: significance of RNF213 as a susceptibility gene. J. Stroke 16, 65–72 (2014).

  143. 143.

    et al. Analysis of cardiovascular phenotype and genotype-phenotype correlation in individuals with a JAG1 mutation and/or Alagille syndrome. Circulation 106, 2567–2574 (2002).

  144. 144.

    et al. Common variants at SCN5A-SCN10A and HEY2 are associated with Brugada syndrome, a rare disease with high risk of sudden cardiac death. Nat. Genet. 45, 1044–1049 (2013).

  145. 145.

    et al. Integrating genetic, transcriptional, and functional analyses to identify 5 novel genes for atrial fibrillation. Circulation 130, 1225–1235 (2014).

  146. 146.

    et al. Genome-wide association study of advanced age-related macular degeneration identifies a role of the hepatic lipase gene (LIPC). Proc. Natl Acad. Sci. USA 107, 7395–7400 (2010).

  147. 147.

    , , & Headache associated with moyamoya disease: a case story and literature review. J. Headache Pain 11, 79–82 (2010).

  148. 148.

    et al. A meta-analysis of thyroid-related traits reveals novel loci and gender-specific differences in the regulation of thyroid function. PLoS Genet. 9, e1003266 (2013).

  149. 149.

    Chronic headache due to masked hypothyroidism. Ann. Intern. Med. 29, 456–460 (1948).

  150. 150.

    , , , & Chronic daily headache: identification of factors associated with induction and transformation. Headache 42, 575–581 (2002).

  151. 151.

    et al. Headache disorders may be a risk factor for the development of new onset hypothyroidism. Headache 57, 21–30 (2017).

  152. 152.

    A genome-wide association study in Europeans and South Asians identifies 5 new loci for coronary artery disease. Circ. Cardiovasc. Genet. 4, 465–466 (2011).

  153. 153.

    et al. Genome-wide association study for coronary artery calcification with follow-up in myocardial infarction. Circulation 124, 2855–2864 (2011).

  154. 154.

    et al. Shared genetic susceptibility to ischemic stroke and coronary artery disease: a genome-wide analysis of common variants. Stroke 45, 24–36 (2014).

  155. 155.

    et al. Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. Nat. Genet. 43, 1082–1090 (2011).

  156. 156.

    et al. Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nat. Genet. 45, 1150–1159 (2013).

  157. 157.

    et al. Genome-wide association study of a heart failure related metabolomic profile among African Americans in the atherosclerosis risk in communities (ARIC) study. Genet. Epidemiol. 37, 840–845 (2013).

  158. 158.

    et al. Genome-wide association study of lung function decline in adults with and without asthma. J. Allergy Clin. Immunol. 129, 1218–1228 (2012).

  159. 159.

    et al. Genome-wide association study identifies 8 novel loci associated with blood pressure responses to interventions in Han Chinese. Circ. Cardiovasc. Genet. 6, 598–607 (2013).

  160. 160.

    et al. Genome-wide meta-analyses identifies seven loci associated with platelet aggregation in response to agonists. Nat. Genet. 42, 608–613 (2010).

  161. 161.

    et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat. Genet. 43, 333–338 (2011).

  162. 162.

    et al. Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nat. Genet. 44, 545–551 (2012).

  163. 163.

    & Neuron-glia interactions of rat hippocampal cells in vitro: glial-guided neuronal migration and neuronal regulation of glial differentiation. J. Neurosci. 10, 1276–1285 (1990).

  164. 164.

    , , & Astn2, a novel member of the astrotactin gene family, regulates the trafficking of ASTN1 during glial-guided neuronal migration. J. Neurosci. 30, 8529–8540 (2010).

  165. 165.

    Strategic approach to fit-for-purpose biomarkers in drug development. Annu. Rev. Pharmacol. Toxicol. 48, 631–651 (2008).

  166. 166.

    et al. Familial hemiplegic migraine: follow-up findings of diffusion-weighted magnetic resonance imaging (MRI), perfusion-MRI and [99mTc] HMPAO-SPECT in a patient with prolonged hemiplegic aura. Cephalalgia 24, 533–539 (2004).

  167. 167.

    et al. Prolonged hemiplegic migraine associated with unilateral hyperperfusion on perfusion weighted magnetic resonance imaging. J. Neurol. Neurosurg. Psychiatry 73, 202–203 (2002).

  168. 168.

    et al. Genetic epidemiology of migraine and depression. Cephalalgia 36, 679–691 (2016).

  169. 169.

    Biology: the big challenges of big data. Nature 498, 255–260 (2013).

  170. 170.

    & Human neuroimaging as a “big data” science. Brain Imaging Behav. 8, 323–331 (2014).

  171. 171.

    Functional interactions as big data in the human brain. Science 342, 580–584 (2013).

  172. 172.

    Consortium of the Human Genome Project. The NIH human connectome project. University of Southern California (2016).

  173. 173.

    , & Imaging genomics. Curr. Opin. Neurol. 23, 368–373 (2010).

  174. 174.

    ENIGMA. Enhancing neuro imaging genetics through meta analysis. University of Southern California (2016).

  175. 175.

    et al. ENIGMA and the individual: predicting factors that affect the brain in 35 countries worldwide. Neuroimage 145, 389–408 (2015).

  176. 176.

    , , & The shape of dendritic arbors in different functional domains of the cortical orientation map. J. Neurosci. 34, 3231–3236 (2014).

  177. 177.

    , , , & Human synaptic plasticity gene expression profile and dendritic spine density changes in HIV-infected human CNS cells: role in HIV-associated neurocognitive disorders (HAND). PLoS ONE 8, e61399 (2013).

  178. 178.

    et al. Detection and interpretation of shared genetic influences on 42 human traits. Nat. Genet. 48, 709–717 (2016).

  179. 179.

    et al. Biochemical changes in the brain of hemiplegic migraine patients measured with 7 tesla 1H-MRS. Cephalalgia 34, 959–967 (2014).

  180. 180.

    , , , & Perfusion and pH MRI in familial hemiplegic migraine with prolonged aura. Cephalalgia 36, 279–283 (2016).

  181. 181.

    , & A case report of sporadic hemiplegic migraine associated cerebral hypoperfusion: comparison of arterial spin labeling and dynamic susceptibility contrast perfusion MR imaging. Eur. J. Pediatr. 175, 295–298 (2016).

  182. 182.

    & Human studies in the pathophysiology of migraine: genetics and functional neuroimaging. Headache 53, 401–412 (2013).

  183. 183.

    et al. The altered right frontoparietal network functional connectivity in migraine and the modulation effect of treatment. Cephalalgia 37, 161–176 (2017).

  184. 184.

    et al. White matter microstructure abnormalities in pediatric migraine patients. Cephalalgia 35, 1278–1286 (2015).

  185. 185.

    et al. A 'complex' of brain metabolites distinguish altered chemistry in the cingulate cortex of episodic migraine patients. Neuroimage Clin. 11, 588–594 (2016).

  186. 186.

    R Development Core Team. The R project for statistical computing. The R Foundation (2017).

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Acknowledgements

D.R.N. is supported in part by a National Health and Medical Research Council (NHMRC) project grant (APP1075175) and the European Union Seventh Framework Programme (2007–2013) under grant agreement no. 602633 (EUROHEADPAIN). D.B. is supported by grants from the NIH (NINDS Grants: K24NS064050, R01NS0750182, RO1 NS073977) and by the Mayday/Louis Herlands Chair for Pain Systems Science and the National Headache Foundation. L.R.G.'s migraine research is supported by NHMRC project grants APP1058808 and APP1083450.

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Affiliations

  1. Institute of Health and Biomedical Innovation, Queensland University of Technology, 60 Musk Avenue, Brisbane, Queensland 4059, Australia.

    • Dale R. Nyholt
    •  & Lyn R. Griffiths
  2. Center for Pain and the Brain, Boston Children's Hospital, 1 Autumn Street, Boston, Massachusetts 02115, USA.

    • David Borsook
  3. Massachusetts General Hospital, CNY 120, 149 13th Street, Boston, Massachusetts 02129, USA.

    • David Borsook

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Contributions

All authors contributed equally to all stages of the preparation of the manuscript.

Competing interests

D.R.N. declares no competing financial interests. L.R.G. consults for Novartis and D.B. consults for Biogen.

Corresponding authors

Correspondence to Dale R. Nyholt or David Borsook or Lyn R. Griffiths.

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DOI

https://doi.org/10.1038/nrneurol.2017.151

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