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Gene-based pleiotropy across migraine with aura and migraine without aura patient groups.

ABSTRACT: It is unclear whether patients diagnosed according to International Classification of Headache Disorders criteria for migraine with aura (MA) and migraine without aura (MO) experience distinct disorders or whether their migraine subtypes are genetically related.Using a novel gene-based (statistical) approach, we aimed to identify individual genes and pathways associated both with MA and MO.Gene-based tests were performed using genome-wide association summary statistic results from the most recent International Headache Genetics Consortium study comparing 4505 MA cases with 34,813 controls and 4038 MO cases with 40,294 controls. After accounting for non-independence of gene-based test results, we examined the significance of the proportion of shared genes associated with MA and MO.We found a significant overlap in genes associated with MA and MO. Of the total 1514 genes with a nominally significant gene-based p value (pgene-based???0.05) in the MA subgroup, 107 also produced pgene-based???0.05 in the MO subgroup. The proportion of overlapping genes is almost double the empirically derived null expectation, producing significant evidence of gene-based overlap (pleiotropy) (pbinomial-test = 1.5?×?10(-4)). Combining results across MA and MO, six genes produced genome-wide significant gene-based p values. Four of these genes (TRPM8, UFL1, FHL5 and LRP1) were located in close proximity to previously reported genome-wide significant SNPs for migraine, while two genes, TARBP2 and NPFF separated by just 259?bp on chromosome 12q13.13, represent a novel risk locus. The genes overlapping in both migraine types were enriched for functions related to inflammation, the cardiovascular system and connective tissue.Our results provide novel insight into the likely genes and biological mechanisms that underlie both MA and MO, and when combined with previous data, highlight the neuropeptide FF-amide peptide encoding gene (NPFF) as a novel candidate risk gene for both types of migraine.

SUBMITTER: Zhao H

PROVIDER: S-EPMC5541777 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Gene-based pleiotropy across migraine with aura and migraine without aura patient groups.

Zhao Huiying H Eising Else E de Vries Boukje B Vijfhuizen Lisanne S LS Anttila Verneri V Winsvold Bendik S BS Kurth Tobias T Stefansson Hreinn H Kallela Mikko M Malik Rainer R Stam Anine H AH Ikram M Arfan MA Ligthart Lannie L Freilinger Tobias T Alexander Michael M Müller-Myhsok Bertram B Schreiber Stefan S Meitinger Thomas T Aromas Arpo A Eriksson Johan G JG Boomsma Dorret I DI van Duijn Cornelia M CM Zwart John-Anker JA Quaye Lydia L Kubisch Christian C Dichgans Martin M Wessman Maija M Stefansson Kari K Chasman Daniel I DI Palotie Aarno A Martin Nicholas G NG Montgomery Grant W GW Ferrari Michel D MD Terwindt Gisela M GM van den Maagdenberg Arn M J M AM Nyholt Dale R DR

Cephalalgia : an international journal of headache 20151208 7

<h4>Introduction</h4>It is unclear whether patients diagnosed according to International Classification of Headache Disorders criteria for migraine with aura (MA) and migraine without aura (MO) experience distinct disorders or whether their migraine subtypes are genetically related.<h4>Aim</h4>Using a novel gene-based (statistical) approach, we aimed to identify individual genes and pathways associated both with MA and MO.<h4>Methods</h4>Gene-based tests were performed using genome-wide associat ...[more]

PMID: 26660531

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Project description:BackgroundCortical spreading depression (CSD) has been considered the prominent theory for migraine with aura (MwA). However, it is also argued that CSD can exist in patients in a silent state, and not manifest as aura. Thus, the MwA classification based on aura may be questionable. This study aimed to capture whole-brain connectome-based imaging markers with identifiable signatures for MwA and migraine without aura (MwoA).MethodsA total of 88 migraine patients (32 MwA) and 49 healthy controls (HC) underwent a diffusion tensor imaging and resting-state functional magnetic resonance imaging scan. The whole-brain structural connectivity (SC) and functional connectivity (FC) analysis was employed to extract imaging features. The extracted features were subjected to an all-relevant feature selection process within cross-validation loops to pinpoint attributes demonstrating substantial efficacy for patient categorization. Based on the identified features, the predictive ability of the random forest classifiers constructed with the 88 migraine patients' sample was tested using an independent sample of 32 migraine patients (eight MwA).ResultsCompared to MwoA and HC, MwA showed two reduced SC and six FC (five increased and one reduced) features [all P<0.01, after false discovery rate (FDR) correction], involving frontal areas, temporal areas, visual areas, amygdala, and thalamus. A total of four imaging features were significantly correlated with clinical rating scales in all patients (r=-0.38 to 0.47, P<0.01, after FDR correction). The predictive ability of the random forest classifiers achieved an accuracy of 78.1% in the external sample to identify MwA.ConclusionsThe whole-brain connectivity features in our results may serve as connectome-based imaging markers for MwA identification. The alterations of SC and FC strength provide possible evidence in further understanding the heterogeneity and mechanism of MwA which may help for patient-specific decision-making.

Dataset Information

Gene-based pleiotropy across migraine with aura and migraine without aura patient groups.

Publications

Gene-based pleiotropy across migraine with aura and migraine without aura patient groups.

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