Abstract
Human facial asymmetry is due to a complex interaction of genetic and environmental factors. To identify genetic influences on facial asymmetry, we developed a method for automated scoring that summarizes local morphology features and their spatial distribution. A genome-wide association study using asymmetry scores from two local symmetry features was conducted and significant genetic associations were identified for one asymmetry feature, including genes thought to play a role in craniofacial disorders and development: NFATC1, SOX5, NBAS, and TCF7L1. These results provide evidence that normal variation in facial asymmetry may be impacted by common genetic variants and further motivate the development of automated summaries of complex phenotypes.
Highlights
The ability to make connections between genetic and phenotypic variation, hinges on phenotypic descriptions that are sufficiently detailed to capture the traits of interest
It is linked to Feingold Syndrome 1, which can result in craniofacial dismorphology including asymmetry, triangular shaped face, and flat nasal tip (Chen et al, 2012)
Asymmetry is the topic of a large number of studies investigating how genetic and environmental factors influence normal development
Summary
The ability to make connections between genetic and phenotypic variation, hinges on phenotypic descriptions that are sufficiently detailed to capture the traits of interest. Methods for automatically phenotyping images and incorporating complex shape information, will be key in understanding the genetic basis of morphology. New approaches such as the BRIM method, developed by Claes et al, have shown the promise of summarizing morphological differences in novel ways to identify genes affecting normal morphology (Claes et al, 2014). The aim of this study is to use automated phenotyping to produce a score of facial asymmetry that incorporates local morphological measurements and their spatial distribution to investigate the genetic basis of facial asymmetry
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