GENOME-WIDE ANALYSIS OF 102,084 MIGRAINE CASES IDENTIFIES 123 RISK LOCI AND SUBTYPE-SPECIFIC RISK ALLELES 173 8 three had P > 0.14, and one was not available in our data (Supplementary Data 3). When we represented each risk locus by its lead variant, i.e., the variant with the smallest P-value, 47 GWS variants were LD-independent (r2 < 0.1) of the 123 lead variants, and with a more stringent threshold (r2 < 0.01), 15 GWS variants remained LD independent of the 123 lead variants (Supplementary Table 5). In addition, we conducted an approximate stepwise conditional analysis for the 123 risk loci (Methods). Since sample sizes per variant varied considerably, we restricted the conditional analysis to variants with similar effective sample sizes to the lead variant. The conditional analysis returned 6 SNPs within the 123 risk loci that remained GWS after conditioning on the lead variants (Supplementary Table 6A,B). Characterization of migraine risk loci We mapped the 123 risk loci to genes by their physical location using the Ensembl Variant Effect Predictor (VEP).34 Of the lead variants, 59% (72/123) were within a transcript of a protein-coding gene, and 80% (99/123) of the loci contained at least one protein-coding gene within 20 kb, and 93% (114/123) within 250 kb (Supplementary Table 3). Five of the 123 lead variants were missense variants (in genes PLCE1, MRGPRE, SERPINA1, ZBTB4 and ZNF462), and 40 more missense variants were in high LD (r2 > 0.6) with the lead variants (Supplementary Table 7A). Of note, three variants with a predicted high impact consequence on protein function were in high LD with the lead variants: (i) a stop gained variant (rs34358) with lead variant rs42854 (r2= 0.85) in gene ANKDD1B, (ii) a splice donor variant (rs66880209) with lead variant rs1472662 (r2= 0.71) in RP11420K8.1, and (iii) a splice acceptor variant (rs11042902) with lead variant rs4910165 (r2= 0.69) in MRVI1 (Supplementary Table 7B). We used stratified LDSC (S-LDSC) to partition migraine heritability by 24 functional genomic annotations.54, 55 We observed enrichment for 10 categories (Supplementary Figure 3 and Supplementary Table 8), with conserved regions showing the highest enrichment (11.2-fold; P = 1.95 × 10-10), followed by coding regions (8.1-fold; P = 1.36 × 10-3) and enhancers (4.2-fold; P = 3.64 × 10-4). Prioritization of candidate genes We mapped the 123 lead variants to genes via expression quantitative trait locus (eQTL) association using the GTEx v837 and data repositories included in FUMA38 at a false discovery rate (FDR) of 5% (Methods). The lead variants were cis-eQTLs for 589 genes (Supplementary Table 9), and variants in high LD with the lead variants were cis-eQTLs for an additional 624 genes (Supplementary Table 10). In total, 84% (103/123) of lead variants were cis-eQTLs for at least one gene. Tibial artery had the highest number (47/123) of lead variants as cis-eQTLs in GTEx v8, and it was the only tissue type where the enrichment was statistically higher (P = 6.37 × 10-6)
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