Genome-wide association study in Japanese females identifies fifteen novel skin-related trait associations

Skin trait variation impacts quality-of-life, especially for females from the viewpoint of beauty. To investigate genetic variation related to these traits, we conducted a GWAS of various skin phenotypes in 11,311 Japanese women and identified associations for age-spots, freckles, double eyelids, straight/curly hair, eyebrow thickness, hairiness, and sweating. In silico annotation with RoadMap Epigenomics epigenetic state maps and colocalization analysis of GWAS and GTEx Project eQTL signals provided information about tissue specificity, candidate causal variants, and functional target genes. Novel signals for skin-spot traits neighboured AKAP1 / MSI 2 (rs17833789; P = 2.2 × 10 −9 ) , BNC 2 (rs10810635; P = 2.1 × 10 −22 ) , HSPA1 2 A (rs12259842; P = 7.1 × 10 −11 ), PPARGC1B (rs251468; P = 1.3 × 10 −21 ), and RAB11FIP 2 (rs10444039; P = 5.6 × 10 −21 ). HSPA1 2 A SNPs were the only protein-coding gene eQTLs identified across skin-spot loci. Double edged eyelid analysis identified that a signal around EMX 2 (rs12570134; P = 8.2 × 10 −15 ) was also associated with expression of EMX 2 and the antisense-RNA gene EMX 2 OS in brain putamen basal ganglia tissue. A known hair morphology signal in EDAR was associated with both eyebrow thickness (rs3827760; P = 1.7 × 10 −9 ) and straight/curly hair (rs260643; P = 1.6 × 10 −103 ). Excessive hairiness signals’ top SNPs were also eQTLs for TBX15 (rs984225; P = 1.6 × 10 −8 ), BCL 2 (rs7226979; P = 7.3 × 10 −11 ), and GCC 2 and LIMS1 (rs6542772; P = 2.2 × 10 −9 ). For excessive sweating, top variants in two signals in chr2:28.82-29.05 Mb (rs56089836; P = 1.7 × 10 −11 ) were eQTLs for either PPP1CB or PLB1 , while a top chr16:48.26–48.45 Mb locus SNP was a known ABCC11 missense variant (rs6500380; P = 6.8 × 10 −10 ). In total, we identified twelve loci containing sixteen association signals, of which fifteen were novel. These findings will help dermatologic researchers better understand the genetic underpinnings of skin-related phenotypic variation in human populations.