Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Spatially dense 3D facial heritability and modules of co-heritability in a father-offspring design

Hoskens, Hanne, Li, Jiarui, Indencleef, Karlijne, Gors, Dorothy, Larmuseau, Maarten H. D., Richmond, Stephen, Zhurov, Alexei I., Hens, Greet, Peeters, Hilde and Claes, Peter 2018. Spatially dense 3D facial heritability and modules of co-heritability in a father-offspring design. Frontiers in Genetics 9 , 554. 10.3389/fgene.2018.00554

[img]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (9MB) | Preview
[img]
Preview
PDF (Datasheet4) - Supplemental Material
Download (7MB) | Preview
[img]
Preview
PDF (Datasheet1) - Supplemental Material
Download (20MB) | Preview
[img]
Preview
PDF (Datasheet2) - Supplemental Material
Download (6MB) | Preview
[img]
Preview
PDF (Datasheet3) - Supplemental Material
Download (5MB) | Preview
[img]
Preview
PDF (Datasheet5) - Supplemental Material
Download (998kB) | Preview
[img]
Preview
PDF (Datasheet8) - Supplemental Material
Download (136kB) | Preview
[img]
Preview
PDF (Datasheet9) - Supplemental Material
Download (91kB) | Preview
[img]
Preview
PDF (Datasheet6) - Supplemental Material
Download (21MB) | Preview
[img]
Preview
PDF (Datasheet7) - Supplemental Material
Download (30MB) | Preview

Abstract

Introduction: The human face is a complex trait displaying a strong genetic component as illustrated by various studies on facial heritability. Most of these start from sparse descriptions of facial shape using a limited set of landmarks. Subsequently, facial features are preselected as univariate measurements or principal components and the heritability is estimated for each of these features separately. However, none of these studies investigated multivariate facial features, nor the co-heritability between different facial features. Here we report a spatially dense multivariate analysis of facial heritability and co-heritability starting from data from fathers and their children available within ALSPAC. Additionally, we provide an elaborate overview of related craniofacial heritability studies. Methods: In total, 3D facial images of 762 father-offspring pairs were retained after quality control. An anthropometric mask was applied to these images to establish spatially dense quasi-landmark configurations. Partial least squares regression was performed and the (co-)heritability for all quasi-landmarks (∼7160) was computed as twice the regression coefficient. Subsequently, these were used as input to a hierarchical facial segmentation, resulting in the definition of facial modules that are internally integrated through the biological mechanisms of inheritance. Finally, multivariate heritability estimates were obtained for each of the resulting modules. Results: Nearly all modular estimates reached statistical significance under 1,000,000 permutations and after multiple testing correction (p ≤ 1.3889 × 10-3), displaying low to high heritability scores. Particular facial areas showing the greatest heritability were similar for both sons and daughters. However, higher estimates were obtained in the former. These areas included the global face, upper facial part (encompassing the nasion, zygomas and forehead) and nose, with values reaching 82% in boys and 72% in girls. The lower parts of the face only showed low to moderate levels of heritability. Conclusion: In this work, we refrain from reducing facial variation to a series of individual measurements and analyze the heritability and co-heritability from spatially dense landmark configurations at multiple levels of organization. Finally, a multivariate estimation of heritability for global-to-local facial segments is reported. Knowledge of the genetic determination of facial shape is useful in the identification of genetic variants that underlie normal-range facial variation.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Dentistry
Publisher: Frontiers
ISSN: 1664-8021
Date of First Compliant Deposit: 19 November 2018
Date of Acceptance: 29 October 2018
Last Modified: 28 Feb 2020 11:00
URI: http://orca-mwe.cf.ac.uk/id/eprint/116899

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics