Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population

Abstract Human craniofacial shape is highly variable yet highly heritable with numerous genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we intr...

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Main Authors: Michiel Vanneste, Hanne Hoskens, Seppe Goovaerts, Harold Matthews, Jay Devine, Jose D. Aponte, Joanne Cole, Mark Shriver, Mary L. Marazita, Seth M. Weinberg, Susan Walsh, Stephen Richmond, Ophir D. Klein, Richard A. Spritz, Hilde Peeters, Benedikt Hallgrímsson, Peter Claes
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-54839-1
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Summary:Abstract Human craniofacial shape is highly variable yet highly heritable with numerous genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the general population. We compare three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores reveals a polygenic basis for facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples, both human and mouse, shows craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing insights into the genetic intersection of complex traits and Mendelian disorders.
ISSN:2041-1723