Impact of low-frequency coding variants on human facial shape

Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individual...
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Autor*in:	Dongjing Liu [verfasserIn] Nora Alhazmi [verfasserIn] Harold Matthews [verfasserIn] Myoung Keun Lee [verfasserIn] Jiarui Li [verfasserIn] Jacqueline T. Hecht [verfasserIn] George L. Wehby [verfasserIn] Lina M. Moreno [verfasserIn] Carrie L. Heike [verfasserIn] Jasmien Roosenboom [verfasserIn] Eleanor Feingold [verfasserIn] Mary L. Marazita [verfasserIn] Peter Claes [verfasserIn] Eric C. Liao [verfasserIn] Seth M. Weinberg [verfasserIn] John R. Shaffer [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Übergeordnetes Werk:	In: Scientific Reports - Nature Portfolio, 2011, 11(2021), 1, Seite 13
Übergeordnetes Werk:	volume:11 ; year:2021 ; number:1 ; pages:13

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1038/s41598-020-80661-y

Katalog-ID:	DOAJ062527800

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allfields	10.1038/s41598-020-80661-y doi (DE-627)DOAJ062527800 (DE-599)DOAJ1f6e2e4e71fb416a9663c9577931071c DE-627 ger DE-627 rakwb eng Dongjing Liu verfasserin aut Impact of low-frequency coding variants on human facial shape 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes. Medicine R Science Q Nora Alhazmi verfasserin aut Harold Matthews verfasserin aut Myoung Keun Lee verfasserin aut Jiarui Li verfasserin aut Jacqueline T. Hecht verfasserin aut George L. Wehby verfasserin aut Lina M. Moreno verfasserin aut Carrie L. Heike verfasserin aut Jasmien Roosenboom verfasserin aut Eleanor Feingold verfasserin aut Mary L. Marazita verfasserin aut Peter Claes verfasserin aut Eric C. Liao verfasserin aut Seth M. Weinberg verfasserin aut John R. Shaffer verfasserin aut In Scientific Reports Nature Portfolio, 2011 11(2021), 1, Seite 13 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:11 year:2021 number:1 pages:13 https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/article/1f6e2e4e71fb416a9663c9577931071c kostenfrei https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 1 13
spelling	10.1038/s41598-020-80661-y doi (DE-627)DOAJ062527800 (DE-599)DOAJ1f6e2e4e71fb416a9663c9577931071c DE-627 ger DE-627 rakwb eng Dongjing Liu verfasserin aut Impact of low-frequency coding variants on human facial shape 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes. Medicine R Science Q Nora Alhazmi verfasserin aut Harold Matthews verfasserin aut Myoung Keun Lee verfasserin aut Jiarui Li verfasserin aut Jacqueline T. Hecht verfasserin aut George L. Wehby verfasserin aut Lina M. Moreno verfasserin aut Carrie L. Heike verfasserin aut Jasmien Roosenboom verfasserin aut Eleanor Feingold verfasserin aut Mary L. Marazita verfasserin aut Peter Claes verfasserin aut Eric C. Liao verfasserin aut Seth M. Weinberg verfasserin aut John R. Shaffer verfasserin aut In Scientific Reports Nature Portfolio, 2011 11(2021), 1, Seite 13 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:11 year:2021 number:1 pages:13 https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/article/1f6e2e4e71fb416a9663c9577931071c kostenfrei https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 1 13
allfields_unstemmed	10.1038/s41598-020-80661-y doi (DE-627)DOAJ062527800 (DE-599)DOAJ1f6e2e4e71fb416a9663c9577931071c DE-627 ger DE-627 rakwb eng Dongjing Liu verfasserin aut Impact of low-frequency coding variants on human facial shape 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes. Medicine R Science Q Nora Alhazmi verfasserin aut Harold Matthews verfasserin aut Myoung Keun Lee verfasserin aut Jiarui Li verfasserin aut Jacqueline T. Hecht verfasserin aut George L. Wehby verfasserin aut Lina M. Moreno verfasserin aut Carrie L. Heike verfasserin aut Jasmien Roosenboom verfasserin aut Eleanor Feingold verfasserin aut Mary L. Marazita verfasserin aut Peter Claes verfasserin aut Eric C. Liao verfasserin aut Seth M. Weinberg verfasserin aut John R. Shaffer verfasserin aut In Scientific Reports Nature Portfolio, 2011 11(2021), 1, Seite 13 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:11 year:2021 number:1 pages:13 https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/article/1f6e2e4e71fb416a9663c9577931071c kostenfrei https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 1 13
allfieldsGer	10.1038/s41598-020-80661-y doi (DE-627)DOAJ062527800 (DE-599)DOAJ1f6e2e4e71fb416a9663c9577931071c DE-627 ger DE-627 rakwb eng Dongjing Liu verfasserin aut Impact of low-frequency coding variants on human facial shape 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes. Medicine R Science Q Nora Alhazmi verfasserin aut Harold Matthews verfasserin aut Myoung Keun Lee verfasserin aut Jiarui Li verfasserin aut Jacqueline T. Hecht verfasserin aut George L. Wehby verfasserin aut Lina M. Moreno verfasserin aut Carrie L. Heike verfasserin aut Jasmien Roosenboom verfasserin aut Eleanor Feingold verfasserin aut Mary L. Marazita verfasserin aut Peter Claes verfasserin aut Eric C. Liao verfasserin aut Seth M. Weinberg verfasserin aut John R. Shaffer verfasserin aut In Scientific Reports Nature Portfolio, 2011 11(2021), 1, Seite 13 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:11 year:2021 number:1 pages:13 https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/article/1f6e2e4e71fb416a9663c9577931071c kostenfrei https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 1 13
allfieldsSound	10.1038/s41598-020-80661-y doi (DE-627)DOAJ062527800 (DE-599)DOAJ1f6e2e4e71fb416a9663c9577931071c DE-627 ger DE-627 rakwb eng Dongjing Liu verfasserin aut Impact of low-frequency coding variants on human facial shape 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes. Medicine R Science Q Nora Alhazmi verfasserin aut Harold Matthews verfasserin aut Myoung Keun Lee verfasserin aut Jiarui Li verfasserin aut Jacqueline T. Hecht verfasserin aut George L. Wehby verfasserin aut Lina M. Moreno verfasserin aut Carrie L. Heike verfasserin aut Jasmien Roosenboom verfasserin aut Eleanor Feingold verfasserin aut Mary L. Marazita verfasserin aut Peter Claes verfasserin aut Eric C. Liao verfasserin aut Seth M. Weinberg verfasserin aut John R. Shaffer verfasserin aut In Scientific Reports Nature Portfolio, 2011 11(2021), 1, Seite 13 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:11 year:2021 number:1 pages:13 https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/article/1f6e2e4e71fb416a9663c9577931071c kostenfrei https://doi.org/10.1038/s41598-020-80661-y kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 1 13
language	English
source	In Scientific Reports 11(2021), 1, Seite 13 volume:11 year:2021 number:1 pages:13
sourceStr	In Scientific Reports 11(2021), 1, Seite 13 volume:11 year:2021 number:1 pages:13
format_phy_str_mv	Article
institution	findex.gbv.de
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container_title	Scientific Reports
authorswithroles_txt_mv	Dongjing Liu @@aut@@ Nora Alhazmi @@aut@@ Harold Matthews @@aut@@ Myoung Keun Lee @@aut@@ Jiarui Li @@aut@@ Jacqueline T. Hecht @@aut@@ George L. Wehby @@aut@@ Lina M. Moreno @@aut@@ Carrie L. Heike @@aut@@ Jasmien Roosenboom @@aut@@ Eleanor Feingold @@aut@@ Mary L. Marazita @@aut@@ Peter Claes @@aut@@ Eric C. Liao @@aut@@ Seth M. Weinberg @@aut@@ John R. Shaffer @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	663366712
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language_de	englisch
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author	Dongjing Liu
spellingShingle	Dongjing Liu misc Medicine misc R misc Science misc Q Impact of low-frequency coding variants on human facial shape
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topic_title	Impact of low-frequency coding variants on human facial shape
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title	Impact of low-frequency coding variants on human facial shape
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title_full	Impact of low-frequency coding variants on human facial shape
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author_browse	Dongjing Liu Nora Alhazmi Harold Matthews Myoung Keun Lee Jiarui Li Jacqueline T. Hecht George L. Wehby Lina M. Moreno Carrie L. Heike Jasmien Roosenboom Eleanor Feingold Mary L. Marazita Peter Claes Eric C. Liao Seth M. Weinberg John R. Shaffer
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title_sort	impact of low-frequency coding variants on human facial shape
title_auth	Impact of low-frequency coding variants on human facial shape
abstract	Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes.
abstractGer	Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes.
abstract_unstemmed	Abstract The contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) in 8091 genes on multi-dimensional facial shape phenotypes in a European cohort of 2329 healthy individuals. Using three-dimensional images, we partitioned the full face into 31 hierarchically arranged segments to model facial morphology at multiple levels, and generated multi-dimensional phenotypes representing the shape variation within each segment. We used MultiSKAT, a multivariate kernel regression approach to scan the exome for face-associated low-frequency variants in a gene-based manner. After accounting for multiple tests, seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology and was predicted bioinformatically to have a deleterious effect on protein function. Notably, NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. Findings from this study expanded our understanding of the genetic basis of normal-range facial shape by highlighting the role of low-frequency coding variants in several novel genes.
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title_short	Impact of low-frequency coding variants on human facial shape
url	https://doi.org/10.1038/s41598-020-80661-y https://doaj.org/article/1f6e2e4e71fb416a9663c9577931071c https://doaj.org/toc/2045-2322
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