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. 2014 May 22;10(5):e1004366.
doi: 10.1371/journal.pgen.1004366. eCollection 2014 May.

Selectivity in Genetic Association With Sub-Classified Migraine in Women

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Free PMC article

Selectivity in Genetic Association With Sub-Classified Migraine in Women

Daniel I Chasman et al. PLoS Genet. .
Free PMC article

Erratum in

Abstract

Migraine can be sub-classified not only according to presence of migraine aura (MA) or absence of migraine aura (MO), but also by additional features accompanying migraine attacks, e.g. photophobia, phonophobia, nausea, etc. all of which are formally recognized by the International Classification of Headache Disorders. It remains unclear how aura status and the other migraine features may be related to underlying migraine pathophysiology. Recent genome-wide association studies (GWAS) have identified 12 independent loci at which single nucleotide polymorphisms (SNPs) are associated with migraine. Using a likelihood framework, we explored the selective association of these SNPs with migraine, sub-classified according to aura status and the other features in a large population-based cohort of women including 3,003 active migraineurs and 18,108 free of migraine. Five loci met stringent significance for association with migraine, among which four were selective for sub-classified migraine, including rs11172113 (LRP1) for MO. The number of loci associated with migraine increased to 11 at suggestive significance thresholds, including five additional selective associations for MO but none for MA. No two SNPs showed similar patterns of selective association with migraine characteristics. At one extreme, SNPs rs6790925 (near TGFBR2) and rs2274316 (MEF2D) were not associated with migraine overall, MA, or MO but were selective for migraine sub-classified by the presence of one or more of the additional migraine features. In contrast, SNP rs7577262 (TRPM8) was associated with migraine overall and showed little or no selectivity for any of the migraine characteristics. The results emphasize the multivalent nature of migraine pathophysiology and suggest that a complete understanding of the genetic influence on migraine may benefit from analyses that stratify migraine according to both aura status and the additional diagnostic features used for clinical characterization of migraine.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Estimates (beta coefficients) for association in the WGHS from logistic models for each of the 12 candidate SNPs as predictors of migraine accompanied by aura or other characteristics (black bars), or not (gray bars).
Significant associations are indicated with “*” (see also Table S4). Model selection results (Tables 3 & 4) are indicated with outlines around each plot as follows: Non-null models selected using the BIC are indicated with a heavy red outline, while non-null models selected using the AIC are indicated with a thin black outline. “Subset” or “inverse subset” models (see Methods) are indicated with a solid outline, “basic” models are indicated with a dotted outline, and “general” models are indicated with a dashed outline. Migraine characteristics considered were aura, pulsating pain ( = pulsate), unilateral pain ( = unipain), phonophobia ( = sound), photophobia ( = light), duration of 4–72 hours ( = longdur), nausea, aggravation by physical activity ( = aggrphys), inhibition of daily activities ( = inhibit), ≥6 attacks/year ( = freq). The rightmost column (actmig) indicates association estimates for active migraineurs, irrespective of status for the characteristics (see Methods). The order of SNPs is derived from clustering as in Figure S1. See also Methods.

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