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

TL;DR

This study uses large-scale 3D facial data from twins and a novel landmarking method to create detailed heritability maps of human face morphology, addressing previous challenges in facial trait heritability estimation.

Contribution

It introduces a new large-scale heritability analysis of face geometry using a novel automated landmarking workflow, GESSA, to improve phenotypic characterization.

Findings

High heritability in specific facial regions

Automated landmarking improves phenotypic accuracy

Detailed heritability maps of face morphology

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 large-scale heritability study of face geometry that aims to address these issues. High-resolution, three-dimensional 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).