Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping

Dimosthenis Tsagkrasoulis; Pirro Hysi; Tim Spector; Giovanni Montana

doi:10.1038/srep45885

Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping

Dimosthenis Tsagkrasoulis, Pirro Hysi, Tim Spector, Giovanni Montana

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Abstract

The human face is a complex trait under strong genetic control, as evidenced by the striking visual
similarity between twins. Nevertheless, heritability estimates of facial traits have often been
surprisingly low or difficult to replicate. Furthermore, the construction of facial phenotypes that
correspond to naturally perceived facial features remains largely a mystery. We present here a largescale
heritability study of face geometry that aims to address these issues. High-resolution, threedimensional
facial models have been acquired on a cohort of 952 twins recruited from the TwinsUK
registry, and processed through a novel landmarking workflow, GESSA (Geodesic Ensemble Surface
Sampling Algorithm). The algorithm places thousands of landmarks throughout the facial surface
and automatically establishes point-wise correspondence across faces. These landmarks enabled us
to intuitively characterize facial geometry at a fine level of detail through curvature measurements,
yielding accurate heritability maps of the human face (www.heritabilitymaps.info).

Original language	English
Article number	45885
Journal	Scientific Reports
Volume	7
DOIs	https://doi.org/10.1038/srep45885
Publication status	Published - 19 Apr 2017

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title = "Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping",

abstract = "The human face is a complex trait under strong genetic control, as evidenced by the striking visualsimilarity between twins. Nevertheless, heritability estimates of facial traits have often beensurprisingly low or difficult to replicate. Furthermore, the construction of facial phenotypes thatcorrespond to naturally perceived facial features remains largely a mystery. We present here a largescaleheritability study of face geometry that aims to address these issues. High-resolution, threedimensionalfacial models have been acquired on a cohort of 952 twins recruited from the TwinsUKregistry, and processed through a novel landmarking workflow, GESSA (Geodesic Ensemble SurfaceSampling Algorithm). The algorithm places thousands of landmarks throughout the facial surfaceand automatically establishes point-wise correspondence across faces. These landmarks enabled usto intuitively characterize facial geometry at a fine level of detail through curvature measurements,yielding accurate heritability maps of the human face (www.heritabilitymaps.info).",

author = "Dimosthenis Tsagkrasoulis and Pirro Hysi and Tim Spector and Giovanni Montana",

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AU - Tsagkrasoulis, Dimosthenis

AU - Hysi, Pirro

AU - Spector, Tim

AU - Montana, Giovanni

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AB - The human face is a complex trait under strong genetic control, as evidenced by the striking visualsimilarity between twins. Nevertheless, heritability estimates of facial traits have often beensurprisingly low or difficult to replicate. Furthermore, the construction of facial phenotypes thatcorrespond to naturally perceived facial features remains largely a mystery. We present here a largescaleheritability study of face geometry that aims to address these issues. High-resolution, threedimensionalfacial models have been acquired on a cohort of 952 twins recruited from the TwinsUKregistry, and processed through a novel landmarking workflow, GESSA (Geodesic Ensemble SurfaceSampling Algorithm). The algorithm places thousands of landmarks throughout the facial surfaceand automatically establishes point-wise correspondence across faces. These landmarks enabled usto intuitively characterize facial geometry at a fine level of detail through curvature measurements,yielding accurate heritability maps of the human face (www.heritabilitymaps.info).

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Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping

Abstract

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