Human Genetics

, Volume 134, Issue 10, pp 1079–1087 | Cite as

Common polygenic variation contributes to risk of migraine in the Norfolk Island population

  • A. J. Rodriguez-Acevedo
  • M. A. Ferreira
  • Miles C. Benton
  • Melanie A. Carless
  • Harald H. Goring
  • Joanne E. Curran
  • John Blangero
  • R. A. Lea
  • L. R. GriffithsEmail author
Original Investigation


Migraine has been defined as a common disabling primary headache disorder. Epidemiology studies have provided with the undeniable evidence of genetic components as active players in the development of the disease under a polygenic model in which multiple risk alleles exert modest individual effects. Our objective was to test the contribution of a polygenic effect to migraine risk in the Norfolk Island population using a panel of SNPs reported to be disease associated in published migraine GWAS. We also investigated whether individual SNPs were associated with gene expression levels measured in whole blood. Polygenic scores were calculated in a total of 285 related individuals (74 cases, 211 controls) from the Norfolk Island using 51 SNPs previously reported to be associated with migraine in published GWAS. The association between polygenic score and migraine case–control status was tested using logistic regression. Results indicate that a migraine polygenic risk score was associated with migraine case–control status in this population (P = 0.016). This supports the hypothesis that multiple SNPs with weak effects collectively contribute to migraine risk in this population. Amongst the SNPs included in the polygenic model, four were associated with the expression of the USMG5 gene, including rs171251 (P = 0.012). Results from this study provide evidence for a polygenic contribution to migraine risk in an isolated population and highlight specific SNPs that regulate the expression of USMG5, a gene critical for mitochondrial function.


Migraine Migraine With Aura Familial Hemiplegic Migraine Maple Syrup Urine Disease Polygenic Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was supported by funding from a National Health and Medical Research Council of Australia project grant. A.J.R.A was supported by a QUT Postgraduate Research Award (QUTPRA) and the Australian Postgraduate Award (APA) Scholarships. M.C.B. was supported by a Corbett Postgraduate Research Scholarship, and R.A.L. was partially supported by a Corbett Research and a Griffith University Areas of Strategic Investment for Chronic Disease Fellowship.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

439_2015_1587_MOESM1_ESM.docx (26 kb)
Supplementary material 1 (DOCX 26 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • A. J. Rodriguez-Acevedo
    • 1
  • M. A. Ferreira
    • 2
  • Miles C. Benton
    • 1
  • Melanie A. Carless
    • 3
  • Harald H. Goring
    • 4
  • Joanne E. Curran
    • 4
  • John Blangero
    • 4
  • R. A. Lea
    • 1
  • L. R. Griffiths
    • 1
    Email author
  1. 1.Genomics Research Centre, Institute of Health and Biomedical InnovationQUTBrisbaneAustralia
  2. 2.QIMR-Berghofer Medical Research InstituteBrisbaneAustralia
  3. 3.Texas Biomedical Research InstituteSan AntonioUSA
  4. 4.South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of MedicineBrownsvilleUSA

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