Genome-Wide Association Study Reveals Multiple Loci Influencing Normal Human Facial Morphology

Abstract

Numerous lines of evidence point to a genetic basis for facial morphology in humans, yet little is known about how specific genetic variants relate to the phenotypic expression of many common facial features. We conducted genome-wide association meta-analyses of 20 quantitative facial measurements derived from the 3D surface images of 3118 healthy individuals of European ancestry belonging to two US cohorts. Analyses were performed on just under one million genotyped SNPs (Illumina OmniExpress+Exome v1.2 array) imputed to the 1000 Genomes reference panel (Phase 3). We observed genome-wide significant associations (p < 5 x 10−8) for cranial base width at 14q21.1 and 20q12, intercanthal width at 1p13.3 and Xq13.2, nasal width at 20p11.22, nasal ala length at 14q11.2, and upper facial depth at 11q22.1. Several genes in the associated regions are known to play roles in craniofacial development or in syndromes affecting the face: MAFB, PAX9, MIPOL1, ALX3, HDAC8, and PAX1. We also tested genotype-phenotype associations reported in two previous genome-wide studies and found evidence of replication for nasal ala length and SNPs in CACNA2D3 and PRDM16. These results provide further evidence that common variants in regions harboring genes of known craniofacial function contribute to normal variation in human facial features. Improved understanding of the genes associated with facial morphology in healthy individuals can provide insights into the pathways and mechanisms controlling normal and abnormal facial morphogenesis.

Genome-wide mapping of global-to-local genetic effects on human facial shape

“…In contrast to a recent GWAS on human body height 41 , which, due to the widespread availability of the phenotype, was able to identify 423 loci in combined samples over two orders of magnitude larger than what was used here, the specialized phenotype data needed for investigating 3D facial shape is limited to a few, smaller cohorts. Using the PITT cohort from Shaffer et al 6 , we managed to substantially increase the number of loci identified. In fact, these results are unmatched by any imaging-based facial GWAS to date.…”

Exploring the Underlying Genetics of Craniofacial Morphology through Various Sources of Knowledge

“…Shaffer et al conducted a GWAS analyzing 20 quantitative facial measurements on 3D images of a cohort of about 3100 American individuals of European descent. They found six regions associated with variable facial traits, in which several genes are located which are known to be associated with craniofacial development: MAFB, PAX9, MIPOL1, ALX3, HDAC8, and PAX1 [56]. Furthermore, they were able to replicate the correlation between nasal ala length and SNPs in CACNA2D3 and PRDM16 and between intercanthal width and SNP rs7559271 in PAX3 .…”

Commentary: Facial Width-to-Height Ratio (fWHR) Is Not Associated with Adolescent Testosterone Levels

“…Generally, it is helpful to control for other factors that might influence an association or the involved variables (Cohen et al, 2003). With respect to testosterone and fWHR, this could include age, body-mass index, genetic influences, and physical health and exercise (e.g., Zitzmann and Nieschlag, 2001; Hehman et al, 2014; Geniole et al, 2015; Shaffer et al, 2016). Therefore, the authors' analysis should include an age covariate, since it is critical to account for strong developmental effects on the variables of interest.…”