Improved polygenic risk prediction in migraine-first patients

Abstract Background Recent meta-analyses estimated 14.6% and 11.2% SNP-based heritability of migraine, compared to twin-heritability estimates of 30–60%. This study aimed to investigate heritability estimates in “migraine-first” individuals, patients for whom G43 (migraine with or without aura) was their first medical diagnosis in their lifetime. Findings Using data from the UK Biobank (N = 199,929), genome-wide association studies (GWAS) were conducted on 6,139 migraine-first patients and 193,790 healthy controls. SNP-based heritability was estimated using SumHer, yielding 19.37% (± 0.019) for all SNPs and 21.31% (± 0.019) for HapMap3 variants, substantially surpassing previous estimates. Key risk loci included PRDM16, FHL5, ASTN2, STAT6/LRP1, and SLC24A3, and pathway analyses highlighted retinol metabolism and steroid hormone biosynthesis as important pathways in these patients. Conclusions The findings underscore that excluding comorbidities at onset time can enhance heritability estimates and genetic signal detection, significantly reducing the extent of “missing heritability” in migraine.