Genome-wide mapping of global-to-local genetic effects on human facial shape
Open accessAbstract
Genome-wide association scans of complex multipartite traits like the human face typically use preselected phenotypic measures. Here we report a data-driven approach to phenotyping facial shape at multiple levels of organization, allowing for an open-ended description of facial variation while preserving statistical power. In a sample of 2,329 persons of European ancestry, we identified 38 loci, 15 of which replicated in an independent European sample (n = 1,719). Four loci were completely new. For the others, additional support (n = 9) or pleiotropic effects (n = 2) were found in the literature, but the results reported here were further refined. All 15 replicated loci highlighted distinctive patterns of global-to-local genetic effects on facial shape and showed enrichment for active chromatin elements in human cranial neural crest cells, suggesting an early developmental origin of the facial variation captured. These results have implications for studies of facial genetics and other complex morphological traits. The authors report a data-driven approach to phenotyping 3D facial shape. They apply their methodology to 2,329 individuals of European ancestry and identify 38 loci that associate with specific facial morphologies, some of which overlap with neural-crest-specific regulatory regions.
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A significant portion of the 16 ear-related loci have been shown to have strong ties to human facial structure.
“A significant portion of the 16 ear-related loci discussed here have been shown to have strong ties to human facial structure [8,15,21,22,30].”
From Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci (2023) · cites this paper as [22]
The Results (Genetic mapping of global-to-local shape; no page given) report replicated loci associated with facial shape. But the paper does not identify these as members of the citing document’s 16 ear-related loci or establish what portion of that set has facial associations. (LLM, conf=0.78)
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An overview of the latest developments in facial imaging
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Self-citationBonfante, B., Faux, P., Navarro, N., Mendoza‐Revilla, J., Dubied, M., Montillot, C., Winchester, E. W., Poloni, L., Varón‐González, C., Jones, P., et al. (2021) · Science Advances · doi:10.1126/sciadv.abc6160 · Cited by 66 · see citing works
Self-citationLimb development genes underlie variation in human fingerprint patterns
Li, J., Glover, J. D., Zhang, H., Peng, M., Tan, J., Mallick, C. B., Hou, D., Yang, Y., Wu, S., Liu, Y., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.008 · Cited by 71 · see citing works
Self-citationShaping faces: genetic and epigenetic control of craniofacial morphogenesis
Selleri, L., & Rijli, F. M. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00594-w · Cited by 68 · see citing works
“…enable fine-tuning of organismal morphology 25,159–162 ; future research based on interspecific hybrids may uncover novel signalling pathways divergently regulated between humans and chimpanzees that underpin facial morphological variation. information contained in 3D facial surface images 110 .”
Genetic variants underlying differences in facial morphology in East Asian and European populations
Zhang, M., Wu, S., Du, S., Qian, W., Chen, J., Qiao, L., Yang, Y., Tan, J., Yuan, Z., Peng, Q., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01038-7 · Cited by 64 · see citing works
Self-citationFaceBase 3: analytical tools and FAIR resources for craniofacial and dental research
Samuels, B. D., Aho, R., Brinkley, J. F., Bugacov, A., Feingold, E., Fisher, S., Gonzalez-Reiche, A. S., Hacia, J. G., Hallgrímsson, B., Hansen, K. L., et al. (2020) · Development · doi:10.1242/dev.191213 · Cited by 53 · see citing works
“Epigenetic landscapes and regulatory divergence of human craniofacial traits (https://doi.org/10.25550/1WWG) Cranial neural crest cells (CNCCs) play major roles duringdevelopment in establishing craniofacial morphology and determining species-specific variation.”
BackgroundInfluentialSelf-citationYankee, T. N., Oh, S., Winchester, E. W., Wilderman, A. S., Robinson, K. R., Gordon, T., Rosenfeld, J. A., VanOudenhove, J., Scott, D. A., Leslie, E. J., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40363-1 · Cited by 51 · see citing works
Self-citationNaqvi, S., Hoskens, H., Wilke, F., Weinberg, S., Shaffer, J., Walsh, S., Shriver, M., Wysocka, J., & Claes, P. (2022) · Annual review of genomics and human genetics (Print) · doi:10.1146/annurev-genom-120121-102607 · Cited by 53 · see citing works
“Indeed, the main modes of variation in the data are effectively described by the first several principal components following principal component analysis, and these modes have been analyzed separately or conjointly in genetic association studies (25, 27, 93, 96, 118, 125, 164).”
BackgroundMethodInfluentialSelf-citationSNPs Associated With Testosterone Levels Influence Human Facial Morphology
Roosenboom, J., Indencleef, K., Lee, M. K., Hoskens, H., White, J. D., Liu, D., Hecht, J. T., Wehby, G. L., Moreno, L. M., Hodges‐Simeon, C. R., et al. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00497 · Cited by 46 · see citing works
Self-citationThe effect of automated landmark identification on morphometric analyses
Percival, C. J., Devine, J., Darwin, B. C., et al. (2019) · Journal of Anatomy · doi:10.1111/joa.12973 · Cited by 45 · see citing works
“Alternate 3D surface-based registration methods use dense clusters of pseudolandmarks, quasi-landmarks or surface vertices to quantify bone (Boyer et al. 2015; Pomidor et al. 2016) and facial morphology (Claes et al. 2011, 2018).”
BackgroundArtificial intelligence in paleontology
Yu, C., Qin, F., Watanabe, A., Yao, W., Li, Y., Qin, Z., Liu, Y., Wang, H., Jiangzuo, Q., Hsiang, A. Y., et al. (2024) · Earth-Science Reviews · doi:10.1016/j.earscirev.2024.104765 · Cited by 49 · see citing works
Craniofacial genetics: Where have we been and where are we going?
Weinberg, S. M., Cornell, R. A., & Leslie, E. J. (2018) · PLoS Genetics · doi:10.1371/journal.pgen.1007438 · Cited by 40 · see citing works
“A recent study [60] using a novel data-driven approach to measuring 3D facial images based on machine learning principles identified 38 genome-wide significant loci, 15 of which were independently replicated.”
BackgroundSelf-citationWu, W., Zhai, G., Xu, Z., Hou, B., Liu, D.-H., Liu, T., Liu, W., & Ren, F. (2019) · Human Genetics · doi:10.1007/s00439-019-02008-6 · Cited by 39 · see citing works
Combining genome-wide association studies highlight novel loci involved in human facial variation
Xiong, Z., Gao, X., Chen, Y., Feng, Z., Pan, S., Lu, H., Uitterlinden, A. G., Nijsten, T., Ikram, A., Rivadeneira, F., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35328-9 · Cited by 37 · see citing works
“Previously, CNCC regulatory activity in face-associated loci has been used to elucidate their functional roles in facial morphogenesis 4,5,17 .”
Impact of DNA source on genetic variant detection from human whole-genome sequencing data
Trost, B., Walker, S., Haider, S. A., Sung, W. W. L., Pereira, S. L., Phillips, C. L., Higginbotham, E. J., Strug, L. J., Nguyen, C. M., Raajkumar, A., et al. (2019) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2019-106281 · Cited by 39 · see citing works
“However, in order for WGS to achieve the broadest possible impact across precision medicine 4 5 and general biology, 6 7 a better understanding of the impact of DNA source is required.”
Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry
Zingaretti, L. M., Monfort, A., & Miguel Pérez-enciso, A. (2021) · Plant Phenomics · doi:10.34133/2021/9812910 · Cited by 39 · see citing works
“Association studies for human 436 shape variations, apple leaf or quantitative analysis for tomato have revealed genes or markers 437 associated with craniofacial shape [28,68,69], leaf variation [70] and tomato morphology [71].”
BackgroundMarks, T. N., Maddux, S. D., Butaric, L. N., & Franciscus, R. G. (2019) · American Journal of Physical Anthropology · doi:10.1002/ajpa.23840 · Cited by 37 · see citing works
Cheng, H., Zhang, Z., Wen, J., Lenstra, J. A., Heller, R., Cai, Y., Guo, Y., Li, M., Li, R., Li, W., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010615 · Cited by 37 · see citing works
Dahal, A., McNevin, D. B., Chikhani, M., & Ward, J. (2023) · Wiley Interdisciplinary Reviews Forensic Science · doi:10.1002/wfs2.1484 · Cited by 44 · see citing works
Li, Q., Chen, J., Faux, P., Delgado, M., Bonfante, B., Fuentes‐Guajardo, M., Mendoza‐Revilla, J., Chacón-Duque, J. C., Hurtado, M., Villegas, V., et al. (2023) · Communications Biology · doi:10.1038/s42003-023-04838-7 · Cited by 36 · see citing works
The Jaw Epidemic: Recognition, Origins, Cures, and Prevention
Kahn, S., Ehrlich, P. R., Feldman, M. W., Sapolsky, R. M., & Wong, S. (2020) · BioScience · doi:10.1093/biosci/biaa073 · Cited by 36 · see citing works
Sources of variation in the 3dMDface and Vectra H1 3D facial imaging systems
White, J. D., Ortega-Castrillón, A., Virgo, C., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-61333-3 · Cited by 32 · see citing works
Self-citationDigital Facial Anthropometry: Application and Implementation
Kukharev, G., & Kaziyeva, N. (2020) · Pattern Recognition and Image Analysis · doi:10.1134/s1054661820030141 · Cited by 30 · see citing works
“Let us point out that solving the problem on searching for GWA the scientists [60–65] worked with an enormous volume of initial measurement information obtained during experiments.”
BackgroundInsights Into the Complexity of Craniofacial Development From a Cellular Perspective
Murillo‐Rincón, A. P., & Kaucká, M. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.620735 · Cited by 30 · see citing works
“In some species such as humans, the otherwise conserved shaping mechanism is flexible enough to allow for shape fine-tuning, resulting in an impressive facial variability (Liu et al., 2012; Adhikari et al., 2016; Cole et al., 2016; Xiong et al., 2019).”
BackgroundThe Era of the Genome and Dental Medicine
Divaris, K. (2019) · Journal of Dental Research · doi:10.1177/0022034519845674 · Cited by 29 · see citing works
Kukla-Bartoszek, M., Szargut, M., Pośpiech, E., Diepenbroek, M., Zielińska, G., Jarosz, A., Piniewska-Róg, D., Arciszewska, J., Cytacka, S., Spólnicka, M., et al. (2020) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2020.102301 · Cited by 25 · see citing works
3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies
Hoskens, H., Liu, D., Naqvi, S., Lee, M. K., Eller, R. J., Indencleef, K., White, J. D., Li, J., Larmuseau, M., Hens, G., et al. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009528 · Cited by 29 · see citing works
“Multivariate methods have been proven to be extremely powerful in dissecting the genetic architecture of craniofacial variation through GWAS for even modest sample sizes [17,25].”
InfluentialSelf-citationA Deep-Learning-Based Method Can Detect Both Common and Rare Genetic Disorders in Fetal Ultrasound
Tang, J., Han, J., Xue, J., Zhen, L., Yang, X., Pan, M., Hu, L., Li, R., Jiang, Y., Zhang, Y., et al. (2023) · Biomedicines · doi:10.3390/biomedicines11061756 · Cited by 30 · see citing works
Look-alike humans identified by facial recognition algorithms show genetic similarities
Joshi, R. S., Rigau, M., García-Prieto, C. A., de Moura, M. C., Piñeyro, D., Morán, S., Dávalos, V., Carrión, P., Ferrando-Bernal, M., Olalde, Í., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111257 · Cited by 28 · see citing works
Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape
Goovaerts, S., Hoskens, H., Eller, R. J., Herrick, N., Musolf, A. M., Justice, C. M., Yuan, M., Naqvi, S., Lee, M. K., Vandermeulen, D., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43237-8 · Cited by 27 · see citing works
“To study genetic effects on cranial vault variation at both a global and local level, we performed a data-driven hierarchical segmentation on symmetrized cranial vault shape, similar to earlier work on facial and brain shape 29,32,33 .”
InfluentialSelf-citationMsx1 deficiency interacts with hypoxia and induces a morphogenetic regulation during lip development
Nakatomi, M., Ludwig, K. U., Knapp, M., Kist, R., Lisgo, S., Ohshima, H., Mangold, E., & Peters, H. (2020) · Development · doi:10.1242/dev.189175 · Cited by 26 · see citing works
CRISPR/Cas gene-editing technology and its advances in dentistry
Chavez‐Granados, P. A., Manisekaran, R., Acosta‐Torres, L. S., & García‐Contreras, R. (2021) · Biochimie · doi:10.1016/j.biochi.2021.12.012 · Cited by 26 · see citing works
Bertól, J. W., Johnston, S., Ahmed, R., Xie, V. K., Hubka, K. M., Cruz, L. A., Nitschke, L., Stetsiv, M., Goering, J. P., Nistor, P., et al. (2022) · Development · doi:10.1242/dev.200068 · Cited by 26 · see citing works
“In addition, as our results highlight, reanalysis of the GWAS data in humans shows that variants near TWIST1 impact normal-range facial shape, including CNCC-derived structures of the midface (Claes et al., 2018; White et al., 2021).”
Self-citationSix NSCL/P Loci Show Associations With Normal-Range Craniofacial Variation
Indencleef, K., Roosenboom, J., Hoskens, H., White, J. D., Shriver, M. D., Richmond, S., Peeters, H., Feingold, E., Marazita, M. L., Shaffer, J. R., et al. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00502 · Cited by 26 · see citing works
Self-citationHunting for genes that shape human faces: Initial successes and challenges for the future
Weinberg, S. M., Roosenboom, J., Shaffer, J. R., Shriver, M. D., Wysocka, J., & Claes, P. D. (2019) · Orthodontics and Craniofacial Research · doi:10.1111/ocr.12268 · Cited by 26 · see citing works
Self-citationCurious about race: Generous methods and modes of knowing in practice
M’Charek, A. A. (2023) · Social Studies of Science · doi:10.1177/03063127231201178 · Cited by 25 · see citing works
“This genetics-driven modelling of the face aims to break with ‘traditional approaches’ to facial morphology, which comes with ‘limitations’ the authors call a ‘phenotype first’ approach in a subsequent publication (Claes et al., 2018).”
BackgroundLiu, C., Lee, M. K., Naqvi, S., Hoskens, H., Liu, D., White, J. D., Indencleef, K., Matthews, H. S., Eller, R. J., Li, J., et al. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009695 · Cited by 28 · see citing works
“3 is a facial-associated locus with accumulated genetic evidence that indicates its role in face formation [3,10,17].”
InfluentialSelf-citationLi, Y., Zhao, W., Li, D., Tao, X., Xiong, Z., Liu, J., Zhang, W., Ji, A., Tang, K., Liu, F., et al. (2019) · Human Genetics · doi:10.1007/s00439-019-02023-7 · Cited by 25 · see citing works
RetractedMorphological evolution in a time of phenomics
Goswami, A., & Clavel, J. (2025) · Paleobiology · doi:10.1017/pab.2024.35 · Cited by 24 · see citing works
“…form and change (Noden 1983; Sears 2004; Sears et al. 2007; Brugmann et al. 2010; Young et al. 2010, 2014; Zhang et al. 2014; Green et al. 2017; Bouwman et al. 2018; Claes et al. 2018; Salzburger 2018; Jebb et al. 2020; Yuan et al. 2021; Zhou et al. 2021; Brandon et al. 2022; Carbeck et al. 2023).”
The Intersection of the Genetic Architectures of Orofacial Clefts and Normal Facial Variation
Indencleef, K., Hoskens, H., Lee, M. K., White, J. D., Liu, C., Eller, R. J., Naqvi, S., Wehby, G. L., Uribe, L. M. M., Hecht, J. T., et al. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.626403 · Cited by 24 · see citing works
Self-citationPredicting Physical Appearance from DNA Data—Towards Genomic Solutions
Pośpiech, E., Teisseyre, P., Mielniczuk, J., & Branicki, W. (2022) · Genes · doi:10.3390/genes13010121 · Cited by 23 · see citing works
“The study by Claes et al. (2018) involved 2329 individuals at the discovery stage and an additional 1719 at the replication stage, and found associations for 15 loci with facial features, including four new genes, nine consistently confirmed, and two linked with pleiotropic facial phenotypic…”
BackgroundThe Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel
Fitzgerald, T. W., Brettell, I., Léger, A., Wolf, N., Kusminski, N., Monahan, J., Barton, C., Herder, C., Aadepu, N., Gierten, J., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02623-z · Cited by 23 · see citing works
Katz, D. C., Aponte, J. D., Liu, W., Green, R. M., Mayeux, J., Pollard, K. M., Pomp, D., Munger, S. C., Murray, S. A., Roseman, C. C., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0233377 · Cited by 21 · see citing works
“Face QTL signals in mouse datasets may be swamped in a whole skull analysis because QTL effect sizes are likely to be small for complex quantitative traits like facial shape [15] and because the most commonly used shape registration algorithm tends to redistribute variation among the coordinates of a landmark configur…”
BackgroundNavic, P., Inthasan, C., Chaimongkhol, T., et al. (2023) · Legal Medicine · doi:10.1016/j.legalmed.2023.102239 · Cited by 22 · see citing works
Genome-wide association study reveals sex-specific genetic architecture of facial attractiveness
Hu, B., Shen, N., Li, J. J., Kang, H., Hong, J., Fletcher, J. M., Greenberg, J. S., Seltzer, M. M., & Lu, Q. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1007973 · Cited by 21 · see citing works
Self-citationA genome-wide association study of facial morphology identifies novel genetic loci in Han Chinese
Huang, Y., Li, D., Qiao, L., Liu, Y., Peng, Q., Wu, S., Zhang, M., Yang, Y., Tan, J., Xu, S., et al. (2020) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2020.10.004 · Cited by 21 · see citing works
“The region has been reported to be associated with chin morphology, but was linked to another candidate gene, ASPM (Claes et al., 2018).”
BackgroundMethodResultInfluentialSelf-citationFeng, Z., Duren, Z., Xiong, Z., Wang, S., Liu, F., Wong, W. H., & Wang, Y. (2021) · Communications Biology · doi:10.1038/s42003-021-01970-0 · Cited by 20 · see citing works
Forensic DNA phenotyping: Inferring phenotypic traits from crime scene DNA.
Dabas, P., Jain, S., Khajuria, H., & Nayak, B. (2022) · Journal of Forensic and Legal Medicine · doi:10.1016/j.jflm.2022.102351 · Cited by 24 · see citing works
Zhang, X., Liu, Q., Zhang, H., Zhao, S., Huang, J., Sovannary, T., Bunnath, L., Aun, H. S., Samnom, H., Su, B., et al. (2021) · National Science Review · doi:10.1093/nsr/nwab072 · Cited by 18 · see citing works
Connecting the dots towards precision orthodontics
Kapila, S., Vora, S. R., Venugopalan, S. R., Elnagar, M. H., & Akyalçın, S. (2023) · Orthodontics and Craniofacial Research · doi:10.1111/ocr.12725 · Cited by 17 · see citing works
“54 57”
Prenatal alcohol exposure and facial morphology in a UK cohort
Howe, L. J., Sharp, G. C., Hemani, G., Zuccolo, L., Richmond, S., & Lewis, S. J. (2019) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2018.11.031 · Cited by 17 · see citing works
Advancement in Human Face Prediction Using DNA
Alshehhi, A., Almarzooqi, A., Alhammadi, K., Werghi, N., Tay, G. K., & AlSafar, H. S. (2023) · Genes · doi:10.3390/genes14010136 · Cited by 18 · see citing works
“Moreover, it is recommended that researchers investigate faces globally and locally by correlating grouped features or measurements with individual or multiple genetic factors [167].”
BackgroundGenetic basis of right and left ventricular heart shape
Burns, R., Young, W. J., Aung, N., Lopes, L. R., Elliot, P. M., Syrris, P., Villa, R. B., Sohrabi, C., Petersen, S. E., Ramírez, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53594-7 · Cited by 16 · see citing works
“Although many aspects of this paper are clearly novel, I do not think the authors can claim to be the first to study the genet basis of heart shape.”
Is the “Habsburg jaw” related to inbreeding?
Vilas, R., Ceballos, F. C., Al‐Soufi, L., González‐García, R., Moreno, C., Moreno, M., Villanueva, L., Ruiz, L., Mateos, J., González, D., et al. (2019) · Annals of Human Biology · doi:10.1080/03014460.2019.1687752 · Cited by 16 · see citing works
“In addition, they suggest a greater sensitivity to inbreeding for the lower third of the face, which is consistent with the modular nature of the human face and differences in heritability between the upper and lower facial parts (Claes et al. 2018; Hoskens et al. 2018).”
BackgroundTFAP2 paralogs regulate midfacial development in part through a conserved ALX genetic pathway
Nguyen, T., Mitchell, J. M., Kiel, M. D., Kenny, C., Li, H., Jones, K. L., Cornell, R. A., Williams, T., Nichols, J. T., & Otterloo, E. V. (2023) · Development · doi:10.1242/dev.202095 · Cited by 15 · see citing works
Individuals with nonsyndromic orofacial clefts have increased asymmetry of fingerprint patterns
Neiswanger, K., Mukhopadhyay, N., Rajagopalan, S. S., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0230534 · Cited by 15 · see citing works
“For example, a number of cleft-related syndromes include limb defects as well (OMIM search term = “cleft lip/palate and limb”, and a recent GWAS study of human facial shape reported that associated loci were enriched for genes involved in limb development [55].”
BackgroundSelf-citationSpatially Dense 3D Facial Heritability and Modules of Co-heritability in a Father-Offspring Design
Hoskens, H., Li, J., Indencleef, K., Gors, D., Larmuseau, M., Richmond, S., Zhurov, A. I., Hens, G., Peeters, H., & Claes, P. D. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00554 · Cited by 15 · see citing works
“Partial least squares regression (PLSR; function plsregress from Matlab 2017b) was performed to predict facial variation in children given the father’s facial variation.”
InfluentialSelf-citationForensic inference of biogeographical ancestry from genotype: The Genetic Ancestry Lab
McNevin, D. B. (2019) · Wiley Interdisciplinary Reviews Forensic Science · doi:10.1002/wfs2.1356 · Cited by 15 · see citing works
Bonazzola, R., Ravikumar, N., Attar, R., Ferrante, E., Syeda-Mahmood, T. F., & Frangi, A. F. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87240-3_67 · Cited by 15 · see citing works
Forensic DNA phenotyping: A promising tool to aid forensic investigation. Current situation
Serrano, A. C. (2020) · Revista Española de Medicina Legal · doi:10.1016/j.remle.2020.01.002 · Cited by 15 · see citing works
Quantification of Facial Traits
Böhringer, S., & de Jong, M. A. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00397 · Cited by 14 · see citing works
“Such quantities are of interest in genome wide association studies (GWASs), syndrome classification, and other prediction settings.”
BackgroundMethodInfluentialSearching for improvements in predicting human eye colour from DNA
Kukla-Bartoszek, M., Teisseyre, P., Pośpiech, E., Karłowska-Pik, J., Zieliński, P., Woźniak, A., Boroń, M., Dąbrowski, M., Zubańska, M., Jarosz, A., et al. (2021) · Zeitschrift für Rechtsmedizin · doi:10.1007/s00414-021-02645-5 · Cited by 16 · see citing works
Muggli, E., Halliday, J., Elliott, E., Penington, A., Thompson, D. K., Spittle, A., Forster, D. A., Lewis, S., Hearps, S. J. C., & Anderson, P. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-054706 · Cited by 9 · see citing works
Dash, S., & Trainor, P. A. (2022) · Development · doi:10.1242/dev.200349 · Cited by 14 · see citing works
Using data‐driven phenotyping to investigate the impact of sex on 3D human facial surface morphology
Matthews, H. S., Mahdi, S. S., Penington, A., Marazita, M. L., Shaffer, J. R., Walsh, S., Shriver, M. D., Claes, P. D., & Weinberg, S. M. (2023) · Journal of Anatomy · doi:10.1111/joa.13866 · Cited by 13 · see citing works
“In 2018, we introduced an innovative extension of spatially dense geometric morphometrics involving the segmentation of 3D facial surfaces into 63 regions or modules based on patterns of multivariate correlation among the ~ 8000 aligned quasi-landmarks (Claes et al., 2018 ).”
MethodSelf-citationAl-baker, B., Alkalaly, A., Ayoub, A. F., Ju, X., & Mossey, P. A. (2023) · European Journal of Orthodontics · doi:10.1093/ejo/cjac077 · Cited by 13 · see citing works
Multilevel principal components analysis of three-dimensional facial growth in adolescents
FARNELL, D. J. J., Richmond, S., Galloway, J., et al. (2019) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2019.105272 · Cited by 13 · see citing works
“Normal facial development (“growth” or “ageing”) begins at conception and can be influenced by genetics with over 50 genes discovered [15-19].”
Self-citationNon-syndromic Cleft Lip and Palate Polymorphisms Affect Normal Lip Morphology
Wilson-Nagrani, C. E., Richmond, S., & Paternoster, L. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00413 · Cited by 13 · see citing works
“More recently, a data driven approach of phenotyping has been described, which successfully identified loci in cranial neural crest cells (Claes et al., 2018).”
BackgroundRedefining the research hospital
Nachev, P., Herron, D., McNally, N., et al. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0201-2 · Cited by 13 · see citing works
Sumiyama, K., & Tanave, A. (2020) · Development, Growth and Differentiation · doi:10.1111/dgd.12671 · Cited by 11 · see citing works
“Regarding craniofacial variations in human, a SNP (rs10238953, A > G mutation, G is minor allele, minor allele frequency is about 0.14) in eDlx#18 cis-regulatory element is associated with non-pathogenic human morphological variation of chin (Claes et al., 2018).”
BackgroundInfluentialPilli, E., Palamenghi, A., & Cattaneo, C. (2025) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.15398 · Cited by 14 · see citing works
Sentinel cells programmed to respond to environmental DNA including human sequences
Nou, X. A., & Voigt, C. A. (2023) · Nature Chemical Biology · doi:10.1038/s41589-023-01431-1 · Cited by 12 · see citing works
“1b and Supplementary Tables 2 and 3) 45,46 .”
Faria‐Teixeira, M. C., Tordera, C., Salvado, F., Carneiro, A. V., & Iglesias‐Linares, A. (2024) · Pediatric Research · doi:10.1038/s41390-023-02907-5 · Cited by 12 · see citing works
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Self-citationMusMorph, a database of standardized mouse morphology data for morphometric meta-analyses
Devine, J., Vidal‐García, M., Liu, W., Neves, A., Vercio, L. L., Green, R. M., Richbourg, H. A., Marchini, M., Unger, C. M., Nickle, A. C., et al. (2022) · Scientific Data · doi:10.1038/s41597-022-01338-x · Cited by 12 · see citing works
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“To do so, we used a Hierarchical Spectral Clustering with Parallel analysis (HPS-CA), a data-driven dimension reduction approach originally developed for the segmentation of human facial features 91,92 .”
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Incisor Occlusion Affects Profile Shape Variation in Middle-Aged Adults
Kanavakis, G., Silvola, A., Halazonetis, D. J., et al. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10040800 · Cited by 11 · see citing works
“The morphology of the lower facial third, in particular, contributes significantly to the variation in facial appearance among humans [4].”
Background
- Authors
- Claes, P., Roosenboom, J., White, J. D., Swigut, T., Sero, D., Li, J., Lee, M. K., Zaidi, A., Mattern, B. C., Liebowitz, C., Pearson, L., González, T., Leslie, E. J., Carlson, J. C., Orlova, E., Suetens, P., Vandermeulen, D., Feingold, E., Marazita, M. L., Shaffer, J. R., Wysocka, J., Shriver, M. D., & Weinberg, S. M.
- Affiliations
- Universitair Ziekenhuis Leuven (BE)
- University of Pittsburgh (US)
- Pennsylvania State University (US)
- Stanford Medicine (US)
- Corresponding author
- Claes, Peter
- Wysocka, Joanna
- Shriver, Mark D.
- Weinberg, Seth M.
- ORCID
- Claes, Peter
- Roosenboom, Jasmien
- White, Julie D.
- Swigut, Tomek
- Sero, Dzemila
- Lee, Myoung Keun
- Zaidi, Arslan
- Mattern, Brooke C.
- Pearson, Laurel
- Leslie, Elizabeth J.
- Carlson, Jenna C.
- Orlova, Ekaterina
- Suetens, Paul
- Vandermeulen, Dirk
- Feingold, Eleanor
- Marazita, Mary L.
- Shaffer, John R.
- Wysocka, Joanna
- Shriver, Mark D.
- Weinberg, Seth M.
- Venue
- Nature Genetics
- Published
- 2018-02-19
- Volume
- 50
- Issue
- 3
- Pages
- 414-423
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC5937280
- OpenAlex
- W2789017128
- Semantic Scholar
- c3fa862579fa588c95e4d3f5a5445fc1c2531c54
- Cited by
- 235
- References
- 62
- Citations by year
- 2026: 21 · 2025: 24 · 2024: 17 · 2023: 31 · 2022: 24 · 2021: 44 · 2020: 29 · 2019: 30 · 2018: 14 · 2015: 1
- FWCI
- 17.94
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Lirias (KU Leuven) (submittedVersion)
- Funders
- KU Leuven
- National Institute of Dental and Craniofacial Research (R01DE027023, R01DE016148, U01DE020078, K99DE025060, R00DE025060, U01DE024430, U01DE020057)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Geometry and Topology › Morphological variations and asymmetry
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- facial shape, facial morphology, genetic loci, cranial neural crest cells, pleiotropy, morphological characters, European ancestry
- MeSH terms
- Adult, Chromosome Mapping, Face, Genotype, Humans, Maxillofacial Development, Phenotype, United States, Cohort Studies, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Quantitative Trait Loci, White People, Genome-Wide Association Study, Young Adult, Genetic Association Studies
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