ArticleThe journal of headache and pain2026
Integrative genetic analysis identifies shared regulation of DNA methylation and gene expression in migraine risk.
Article in The journal of headache and pain, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMigraine affects approximately 14% of adults, but the molecular mechanisms underlying susceptibility remain incompletely understood. Although genome-wide association studies (GWAS) have identified many migraine risk loci, translating these associations into biological insight remains challenging. Environmental and physiological migraine triggers, including hormones, diet and stress, may act partly through epigenetic mechanisms such as DNA methylation. Because many migraine risk variants are non-coding and may influence disease through regulatory effects, integrating genetic association data with DNA methylation and gene expression may help refine migraine-associated loci into candidate molecular mechanisms.
methodsWe performed a novel methylome-wide association study (meWAS) of migraine, imputing genetically regulated DNA methylation at 86,518 cytosine-phosphate-guanine (CpG) sites using GWAS summary statistics derived from 102,084 migraine cases and 771,257 controls of European ancestry. We then linked DNA methylation signals to imputed gene expression using transcriptome-wide association study (TWAS) evidence across 49 Genotype-Tissue Expression tissues. Bayesian colocalisation analyses were used to prioritise CpGs and genes supported by shared causal variants with migraine risk, and to map shared regulatory signals between methylation and expression quantitative trait loci.
resultsWe identified 258 migraine-associated CpG sites after Bonferroni correction (P < 5.78 × 10
conclusionsThese findings show that migraine susceptibility is partly shaped by shared genetic regulation of DNA methylation and gene expression. By refining GWAS loci into candidate genes and molecular signals, this integrative multi-omic framework highlights distributed molecular pathways relevant to neuronal and vascular responsiveness and identifies candidates for future functional characterisation.
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