Genome-wide association study of facial morphology reveals novel associations with FREM1 and PARK2.

Myoung Keun Lee,John R Shaffer,Seth M Weinberg,Ekaterina Orlova,Eleanor Feingold,Elizabeth J Leslie,Mary L Marazita,Jenna C Carlson,Yun Li

doi:10.1371/journal.pone.0176566

Myoung Keun Lee, John R Shaffer + Show 7 more

Open Access

https://doi.org/10.1371/journal.pone.0176566

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Journal: PloS one	Publication Date: Apr 25, 2017
Citations: 67	License type: CC BY 4.0

Affiliation: University of Pittsburgh

Abstract

Several studies have now shown evidence of association between common genetic variants and quantitative facial traits in humans. The reported associations generally involve simple univariate measures and likely represent only a small fraction of the genetic loci influencing facial morphology. In this study, we applied factor analysis to a set of 276 facial linear distances derived from 3D facial surface images of 2187 unrelated individuals of European ancestry. We retained 23 facial factors, which we then tested for genetic associations using a genome-wide panel of 10,677,593 single nucleotide polymorphisms (SNPs). In total, we identified genome-wide significant (p < 5 × 10−8) associations in three regions, including two that are novel: one involving measures of midface height at 6q26 within an intron of PARK2 (lead SNP rs9456748; p = 4.99 × 10−8) and another involving measures of central upper lip height at 9p22 within FREM1 (lead SNP rs72713618; p = 2.02 × 10−8). In both cases, the genetic association was stronger with the composite facial factor phenotype than with any of the individual linear distances that comprise those factors. While the biological role of PARK2 in the craniofacial complex is currently unclear, there is evidence from both mouse models and Mendelian syndromes that FREM1 may influence facial variation. These results highlight the potential value of data-driven multivariate phenotyping for genetic studies of human facial morphology.

Highlights

A number of studies have reported associations between genetic variants and normal-range variation in facial morphology
Paternoster et al [4] applied factor analysis to a set of linear distances and landmark coordinate vectors, while Liu et al [5] based their genome-wide association studies (GWASs) on principal components of shape derived from facial landmark coordinate data
We applied factor analysis to a set of 276 facial linear distances derived from 3D facial surface images and tested the resulting composite phenotypes for genetic associations using a genome-wide panel of single nucleotide polymorphisms (SNPs)

Summary

Introduction

A number of studies have reported associations between genetic variants and normal-range variation in facial morphology. Univariate tests involving simple linear distances or qualitatively graded facial features have generally shown the greatest success in GWAS designs Such measures are often correlated, as the human craniofacial complex shows strong evidence of morphological integration [9]. Paternoster et al [4] applied factor analysis to a set of linear distances and landmark coordinate vectors, while Liu et al [5] based their GWAS on principal components of shape derived from facial landmark coordinate data Neither of these studies detected genome-wide significant associations based on the phenotypes derived. We applied factor analysis to a set of 276 facial linear distances derived from 3D facial surface images and tested the resulting composite phenotypes for genetic associations using a genome-wide panel of single nucleotide polymorphisms (SNPs)

Materials and methods

Results

Discussion