Open Access3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies
Author(s) -
Hanne Hoskens,
Dongjing Liu,
Sahin Naqvi,
Myoung Keun Lee,
Ryan J. Eller,
Karlijne Indencleef,
Julie D. White,
Jiarui Li,
Maarten Larmuseau,
Greet Hens,
Joanna Wysocka,
Susan Walsh,
Stephen Richmond,
Mark D. Shriver,
John R. Shaffer,
Hilde Peeters,
Seth M. Weinberg,
Peter Claes
Publication year - 2021
Publication title -
plos genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.587
H-Index - 233
eISSN - 1553-7404
pISSN - 1553-7390
DOI - 10.1371/journal.pgen.1009528
Subject(s) - biology , craniofacial , genetic architecture , heritability , biometrics , genetics , evolutionary biology , genome wide association study , sibling , univariate , phenotype , computational biology , multivariate statistics , gene , artificial intelligence , developmental psychology , psychology , computer science , genotype , machine learning , single nucleotide polymorphism
The analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17–0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.