Novel Hypotheses Emerging from GWAS in Migraine?
Overview
Affiliations
Recent technical advances in genetics made large-scale genome-wide association studies (GWAS) in migraine feasible and have identified over 40 common DNA sequence variants that affect risk for migraine types. Most of the variants, which are all single nucleotide polymorphisms (SNPs), show robust association with migraine as evidenced by the fact that the vast majority replicate in subsequent independent studies. However, despite thorough bioinformatic efforts aimed at linking the migraine risk SNPs with genes and their molecular pathways, there remains quite some discussion as to how successful this endeavour has been, and their current practical use for the diagnosis and treatment of migraine patients. Although existing genetic information seems to favour involvement of vascular mechanisms, but also neuronal and other mechanisms such as metal ion homeostasis and neuronal migration, the complexity of the underlying genetic pathophysiology presents challenges to advancing genetic knowledge to clinical use. A major issue is to what extent one can rely on bioinformatics to pinpoint the actual disease genes, and from this the linked pathways. In this Commentary, we will provide an overview of findings from GWAS in migraine, current hypotheses of the disease pathways that emerged from these findings, and some of the major drawbacks of the approaches used to identify the genes and pathways. We argue that more functional research is urgently needed to turn the hypotheses that emerge from GWAS in migraine to clinically useful information.
Chen Q, Meng R, Ko C Front Aging Neurosci. 2024; 16:1455858.
PMID: 39416954 PMC: 11480567. DOI: 10.3389/fnagi.2024.1455858.
A cross-tissue transcriptome-wide association study reveals novel susceptibility genes for migraine.
Gui J, Yang X, Tan C, Wang L, Meng L, Han Z J Headache Pain. 2024; 25(1):94.
PMID: 38840241 PMC: 11151630. DOI: 10.1186/s10194-024-01802-6.
Genome Wide Association Study of Neuropathic Ocular Pain.
Huang J, Rodriguez D, Slifer S, Martin E, Levitt R, Galor A Ophthalmol Sci. 2023; 4(2):100384.
PMID: 37868788 PMC: 10587615. DOI: 10.1016/j.xops.2023.100384.
Integrating eQTL and GWAS data characterises established and identifies novel migraine risk loci.
Ghaffar A, Nyholt D Hum Genet. 2023; 142(8):1113-1137.
PMID: 37245199 PMC: 10449685. DOI: 10.1007/s00439-023-02568-8.
Rare Coding Variants in Patients with Non-Syndromic Vestibular Dysfunction.
Sumalde A, Scholes M, Kalmanson O, Terhune E, Frejo L, Wethey C Genes (Basel). 2023; 14(4).
PMID: 37107589 PMC: 10137884. DOI: 10.3390/genes14040831.