3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies

Hanne Hoskens; Dongjing Liu; Sahin Naqvi; Myoung Keun Lee; Ryan J. Eller; Karlijne Indencleef; Julie D. White; Jiarui Li; Maarten H.D. Larmuseau; Greet Hens; Joanna Wysocka; Susan Walsh; Stephen Richmond; Mark D. Shriver; John R. Shaffer; Hilde Peeters; Seth M. Weinberg; Peter Claes

doi:10.1371/journal.pgen.1009528

3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies

Hanne Hoskens, Dongjing Liu, Sahin Naqvi, Myoung Keun Lee, Ryan J. Eller, Karlijne Indencleef, Julie D. White, Jiarui Li, Maarten H.D. Larmuseau, Greet Hens, Joanna Wysocka, Susan Walsh, Stephen Richmond, Mark D. Shriver, John R. Shaffer, Hilde Peeters, Seth M. Weinberg, Peter Claes

Anthropology

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

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.

Original language	English (US)
Article number	e1009528
Journal	PLoS genetics
Volume	17
Issue number	5 May
DOIs	https://doi.org/10.1371/journal.pgen.1009528
State	Published - May 13 2021

All Science Journal Classification (ASJC) codes

Ecology, Evolution, Behavior and Systematics
Molecular Biology
Genetics
Genetics(clinical)
Cancer Research

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Hoskens, H., Liu, D., Naqvi, S., Lee, M. K., Eller, R. J., Indencleef, K., White, J. D., Li, J., Larmuseau, M. H. D., Hens, G., Wysocka, J., Walsh, S., Richmond, S., Shriver, M. D., Shaffer, J. R., Peeters, H., Weinberg, S. M., & Claes, P. (2021). 3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies. PLoS genetics, 17(5 May), [e1009528]. https://doi.org/10.1371/journal.pgen.1009528

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title = "3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies",

abstract = "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.",

author = "Hanne Hoskens and Dongjing Liu and Sahin Naqvi and Lee, {Myoung Keun} and Eller, {Ryan J.} and Karlijne Indencleef and White, {Julie D.} and Jiarui Li and Larmuseau, {Maarten H.D.} and Greet Hens and Joanna Wysocka and Susan Walsh and Stephen Richmond and Shriver, {Mark D.} and Shaffer, {John R.} and Hilde Peeters and Weinberg, {Seth M.} and Peter Claes",

note = "Publisher Copyright: {\textcopyright} 2021 Hoskens et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",

year = "2021",

month = may,

day = "13",

doi = "10.1371/journal.pgen.1009528",

language = "English (US)",

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Hoskens, H, Liu, D, Naqvi, S, Lee, MK, Eller, RJ, Indencleef, K, White, JD, Li, J, Larmuseau, MHD, Hens, G, Wysocka, J, Walsh, S, Richmond, S, Shriver, MD, Shaffer, JR, Peeters, H, Weinberg, SM & Claes, P 2021, '3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies', PLoS genetics, vol. 17, no. 5 May, e1009528. https://doi.org/10.1371/journal.pgen.1009528

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AU - Hoskens, Hanne

AU - Liu, Dongjing

AU - Naqvi, Sahin

AU - Lee, Myoung Keun

AU - Eller, Ryan J.

AU - Indencleef, Karlijne

AU - White, Julie D.

AU - Li, Jiarui

AU - Larmuseau, Maarten H.D.

AU - Hens, Greet

AU - Wysocka, Joanna

AU - Walsh, Susan

AU - Richmond, Stephen

AU - Shriver, Mark D.

AU - Shaffer, John R.

AU - Peeters, Hilde

AU - Weinberg, Seth M.

AU - Claes, Peter

N1 - Publisher Copyright: © 2021 Hoskens et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2021/5/13

Y1 - 2021/5/13

N2 - 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.

AB - 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.

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ER -

3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies

Abstract

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