Genetic evidence for facial variation being a composite phenotype of cranial variation and facial soft tissue thickness

Wei Qian; Manfei Zhang; Kaiwen Wan; Yunxia Xie; Siyuan Du; Jiarui Li; Xiongzheng Mu; Jiange Qiu; Xiangyang Xue; Xiahai Zhuang; Yingzhi Wu; Fan Liu; Sijia Wang

doi:10.1016/j.jgg.2022.02.020

Volume 49 Issue 10

Oct. 2022

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Article Navigation > Journal of Genetics and Genomics > 2022 > 49(10): 934-942

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Genetic evidence for facial variation being a composite phenotype of cranial variation and facial soft tissue thickness

doi: 10.1016/j.jgg.2022.02.020

a. State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201203, China;
b. School of Computer Science, Fudan University, Shanghai 200438, China;
c. CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China;
d. School of Data Science, Fudan University, Shanghai 200433, China;
e. Academy of Medical Science, Zhengzhou University, Zhengzhou, Henan 450052, China;
f. Department of Plastic Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China;
g. CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, University of Chinese Academy of Sciences, Beijing 100101, China;
h. School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China;
i. Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China

Funds:

National Key Research and Development Project (2018YFC0910403)

CAS Interdisciplinary Innovation Team Project

We thank for all suggestions collected during the poster exhibition of the Society for Craniofacial Genetics and Developmental Biology (SCGDB) 2019 Annual Meeting. We thank all the participants in these studies. This project was supported by the following grants and contracts: Strategic Priority Research Program of Chinese Academy of Sciences (XDB38020400, XDB38010400, XDC01000000)

China Postdoctoral Science Foundation (2019M651352, 2020M670984). Service Network Initiative of Chinese Academy of Sciences (KFJ-STS-ZDTP-079).

Science and Technology National Natural Science Foundation of China (31900408, 81930056)

Max Planck-CAS Paul Gerson Unna Independent Research Group Leadership Award

Shanghai Municipal Science and Technology Major Project (2017SHZDZX01, 2018SHZDZX01)

Received Date: 2021-09-16
Accepted Date: 2022-02-20
Rev Recd Date: 2022-02-17
Publish Date: 2022-03-05

Abstract

Abstract

Facial and cranial variation represent a multidimensional set of highly correlated and heritable phenotypes. Little is known about the genetic basis explaining this correlation. We develop a software package ALoSFL for simultaneous localization of facial and cranial landmarks from head computed tomography (CT) images, apply it in the analysis of head CT images of 777 Han Chinese women, and obtain a set of phenotypes representing variation in face, skull and facial soft tissue thickness (FSTT). Association analysis of 301 single nucleotide polymorphisms (SNPs) from 191 distinct genomic loci previously associated with facial variation reveals an unexpected larger number of loci showing significant associations (P < 1e–3) with cranial phenotypes than expected under the null (O/E = 3.39), suggesting facial and cranial phenotypes share a substantial proportion of genetic components. Adding FSTT to a SNP-only model shows a large impact in explaining facial variance. A gene ontology analysis reveals that bone morphogenesis and osteoblast differentiation likely underlie our cranial-significant findings. Overall, this study simultaneously investigates the genetic effects on both facial and cranial variation of the same sample, supporting that facial variation is a composite phenotype of cranial variation and FSTT.
- Facial variation,
- Cranial variation,
- Association analysis,
- Single nucleotide polymorphism,
- Facial soft tissue thickness,
- Computed tomography

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References(55)

References

Adhikari, K., Fuentes-Guajardo, M., Quinto-Sanchez, M., Mendoza-Revilla, J., Camilo Chacon-Duque, J., Acuna-Alonzo, V., Jaramillo, C., Arias, W., Lozano, R.B., Perez, G.M., et al., 2016. A genome-wide association scan implicates DCHS2, RUNX2, GLI3, PAX1 and EDAR in human facial variation. Nat. Commun. 7, 11616

Albert, A.M., Ricanek, K.,Patterson, E., 2007. A review of the literature on the aging adult skull and face:Implications for forensic science research and applications. Forensic Sci. Int. 172, 1-9

Baillie, L.J., Muirhead, J.C., Blyth, P., Niven, B.E.,Dias, G.J., 2016. Position Effect on Facial Soft Tissue Depths:A Sonographic Investigation. J Forensic Sci. 61, S60-S70

Bonfante, B., Faux, P., Navarro, N., Mendoza-Revilla, J., Dubied, M., Montillot, C., Wentworth, E., Poloni, L., Varon-Gonzalez, C., Jones, P., et al., 2021. A GWAS in Latin Americans identifies novel face shape loci, implicating VPS13B and a Denisovan introgressed region in facial variation. Sci. Adv. 7

Bult, C.J., Blake, J.A., Smith, C.L., Kadin, J.A., Richardson, J.E., Anagnostopoulos, A., Asabor, R., Baldarelli, R.M., Beal, J.S., Bello, S.M., et al., 2019. Mouse Genome Database (MGD) 2019. Nucleic Acids Res. 47, D801-D806

Bulut, O., Gungor, K., Thiemann, N., Hizliol, I., Gurcan, S., Hekimoglu, B., Kaya, E., Ozdede, M.,Akay, G., 2017. Repeatability of facial soft tissue thickness measurements for forensic facial reconstruction using X-ray images. Aust. J. Forensic Sci. 49, 134-141

Calloni, G.W., Le Douarin, N.M.,Dupin, E., 2009. High frequency of cephalic neural crest cells shows coexistence of neurogenic, melanogenic, and osteogenic differentiation capacities. Proc. Natl. Acad. Sci. U. S. A. 106, 8947-8952

Cha, S., Lim, J.E., Park, A.Y., Do, J.H., Lee, S.W., Shin, C., Cho, N.H., Kang, J.O., Nam, J.M., Kim, J.S., et al., 2018. Identification of five novel genetic loci related to facial morphology by genome-wide association studies. BMC Genomics 19, 481

Chen, G., Xu, H., Yao, Y., Xu, T., Yuan, M., Zhang, X., Lv, Z.,Wu, M., 2020. BMP Signaling in the Development and Regeneration of Cranium Bones and Maintenance of Calvarial Stem Cells. Front. Cell Dev. Biol. 8, 135-135

Chen, Y., Branicki, W., Walsh, S., Nothnagel, M., Kayser, M., Liu, F.,Consortium, V., 2021. The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits. Forensic Sci. Int.-Gen. 50

Claes, P., Liberton, D.K., Daniels, K., Rosana, K.M., Quillen, E.E., Pearson, L.N., McEvoy, B., Bauchet, M., Zaidi, A.A., Yao, W., et al., 2014. Modeling 3D facial shape from DNA. PLoS Genet. 10, e1004224

Claes, P., Roosenboom, J., White, J.D., Swigut, T., Sero, D., Li, J., Lee, M.K., Zaidi, A., Mattern, B.C., Liebowitz, C., et al., 2018. Genome-wide mapping of global-to-local genetic effects on human facial shape. Nat. Genet. 50, 414-423

Cole, J.B., Manyama, M., Kimwaga, E., Mathayo, J., Larson, J.R., Liberton, D.K., Lukowiak, K., Ferrara, T.M., Riccardi, S.L., Li, M., et al., 2016. Genome wide Association Study of African Children Identifies Association of SCHIP1 and PDE8A with Facial Size and Shape. PLoS Genet. 12, e1006174

Cole, J.B., Manyama, M., Larson, J.R., Liberton, D.K., Ferrara, T.M., Riccardi, S.L., Li, M., Mio, W., Klein, O.D., Santorico, S.A., et al., 2017. Human Facial Shape and Size Heritability and Genetic Correlations. Genetics 205, 967-978

Crouch, D.J.M., Winney, B., Koppen, W.P., Christmas, W.J., Hutnik, K., Day, T., Meena, D., Boumertit, A., Hysi, P., Nessa, A., et al., 2018. Genetics of the human face:Identification of large-effect single gene variants. Proc. Natl. Acad. Sci. U. S. A. 115, E676-E685

De Greef, S., Claes, P., Vandermeulen, D., Mollemans, W., Suetens, P.,Willems, G., 2006. Large-scale in-vivo Caucasian facial soft tissue thickness database for craniofacial reconstruction. Forensic Sci. Int. 159 Suppl 1, S126-146

Delaneau, O., Marchini, J.,Zagury, J.F., 2011. A linear complexity phasing method for thousands of genomes. Nat. Methods 9, 179-181

Dryden, I.L.,Mardia, K.V., 2016. Statistical shape analysis with applications in R, Second edition. ed. Wiley, Chichester, UK

Duan, F.Q., Yang, Y.C., Li, Y., Tian, Y., Lu, K., Wu, Z.K.,Zhou, M.Q., 2014. Skull Identification via Correlation Measure Between Skull and Face Shape. IEEE T. Inf. Foren. Sec. 9, 1322-1332

Elouej, S., Harhouri, K., Le Mao, M., Baujat, G., Nampoothiri, S., Kayserili, H., Al Menabawy, N., Selim, L., Paneque, A.L., Kubisch, C., et al., 2020. Loss of MTX2 causes mandibuloacral dysplasia and links mitochondrial dysfunction to altered nuclear morphology (vol. Nat. Commun. 11

Genomes Project, C., Auton, A., Brooks, L.D., Durbin, R.M., Garrison, E.P., Kang, H.M., Korbel, J.O., Marchini, J.L., McCarthy, S., McVean, G.A., et al., 2015. A global reference for human genetic variation. Nature 526, 68-74

Gottesman, I.I.,Gould, T.D., 2003. The endophenotype concept in psychiatry:Etymology and strategic intentions. Am. J. Psychiat. 160, 636-645

Greenwood, T.A., Lazzeroni, L.C., Maihofer, A.X., Swerdlow, N.R., Calkins, M.E., Freedman, R., Green, M.F., Light, G.A., Nievergelt, C.M., Nuechterlein, K.H., et al., 2019. Genome-wide Association of Endophenotypes for Schizophrenia From the Consortium on the Genetics of Schizophrenia (COGS) Study. JAMA Psychiat. 76, 1274-1284

Howie, B.N., Donnelly, P.,Marchini, J., 2009. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529

Huang, Y., Li, D., Qiao, L., Liu, Y., Peng, Q., Wu, S., Zhang, M., Yang, Y., Tan, J., Xu, S., et al., 2020. A genome-wide association study of facial morphology identifies novel genetic loci in Han Chinese. J. Genet. Genomics. 48, 198-207

Hwang, H.S., Choe, S.Y., Hwang, J.S., Moon, D.N., Hou, Y., Lee, W.J.,Wilkinson, C., 2015. Reproducibility of Facial Soft Tissue Thickness Measurements Using Cone-Beam CT Images According to the Measurement Methods. J. Forensic Sci. 60, 957-965

Kim, S.H.,Shin, H.S., 2018. Three-Dimensional Analysis of the Correlation Between Soft Tissue and Bone of the Lower Face Using Three-Dimensional Facial Laser Scan. J. Craniofac. Surg. 29, 2048-2054

Lee, M.K., Shaffer, J.R., Leslie, E.J., Orlova, E., Carlson, J.C., Feingold, E., Marazita, M.L.,Weinberg, S.M., 2017. Genome-wide association study of facial morphology reveals novel associations with FREM1 and PARK2. PLoS One 12, e0176566

Li, J.,Ji, L., 2005. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 95, 221-227

Li, Y., Zhao, W., Li, D., Tao, X., Xiong, Z., Liu, J., Zhang, W., Ji, A., Tang, K., Liu, F., et al., 2019. EDAR, LYPLAL1, PRDM16, PAX3, DKK1, TNFSF12, CACNA2D3, and SUPT3H gene variants influence facial morphology in a Eurasian population. Hum. Genet. 138, 681-689

Lippert, C., Sabatini, R., Maher, M.C., Kang, E.Y., Lee, S., Arikan, O., Harley, A., Bernal, A., Garst, P., Lavrenko, V., et al., 2017. Identification of individuals by trait prediction using whole-genome sequencing data. Proc. Natl. Acad. Sci. U. S. A. 114, E8800-E8800

Liu, F., van der Lijn, F., Schurmann, C., Zhu, G., Chakravarty, M.M., Hysi, P.G., Wollstein, A., Lao, O., de Bruijne, M., Ikram, M.A., et al., 2012. A genome-wide association study identifies five loci influencing facial morphology in Europeans. PLoS Genet. 8, e1002932

Massey, F.J., 1951. The Kolmogorov-Smirnov Test for Goodness of Fit. J. Am. Stat. Assoc. 46, 68-78

Miller, G.A.,Rockstroh, B.S. 2016. Chapter 2-Progress and Prospects for Endophenotypes for Schizophrenia in the Time of Genomics, Epigenetics, Oscillatory Brain Dynamics, and the Research Domain Criteria, in:Abel, T., Nickl-Jockschat, T. (Eds.), The Neurobiology of Schizophrenia. Academic Press, San Diego, pp. 17-38

Montufar, J., Romero, M.,Scougall-Vilchis, R.J., 2018. Automatic 3-dimensional cephalometric landmarking based on active shape models in related projections. Am. J. Orthod. Dentofac. 153, 449-458

Paternoster, L., Zhurov, A.I., Toma, A.M., Kemp, J.P., St Pourcain, B., Timpson, N.J., McMahon, G., McArdle, W., Ring, S.M., Smith, G.D., et al., 2012. Genome-wide association study of three-dimensional facial morphology identifies a variant in PAX3 associated with nasion position. Am. J. Hum. Genet. 90, 478-485

Pickrell, J.K., Berisa, T., Liu, J.Z., Segurel, L., Tung, J.Y.,Hinds, D.A., 2016. Detection and interpretation of shared genetic influences on 42 human traits. Nat. Genet. 48, 709-717

Preston, G.A.,Weinberger, D.R., 2005. Intermediate phenotypes in schizophrenia:a selective review. Dialogues Clin. Neurosci. 7, 165-179

Qiao, L., Yang, Y., Fu, P., Hu, S., Zhou, H., Peng, S., Tan, J., Lu, Y., Lou, H., Lu, D., et al., 2018. Genome-wide variants of Eurasian facial shape differentiation and a prospective model of DNA based face prediction. J. Genet. Genomics. 45, 419-432

Seselj, M., Duren, D.L.,Sherwood, R.J., 2015. Heritability of the Human Craniofacial Complex. Anat. Rec. 298, 1535-1547

Shaffer, J.R., Orlova, E., Lee, M.K., Leslie, E.J., Raffensperger, Z.D., Heike, C.L., Cunningham, M.L., Hecht, J.T., Kau, C.H., Nidey, N.L., et al., 2016. Genome-Wide Association Study Reveals Multiple Loci Influencing Normal Human Facial Morphology. PLoS Genet. 12, e1006149

Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B.,Ideker, T., 2003. Cytoscape:a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498-2504

Simmons-Ehrhardt, T., Falsetti, C., Falsetti, A.B.,Ehrhardt, C.J., 2018. Open-Source Tools for Dense Facial Tissue Depth Mapping of Computed Tomography Models. Hum. Biol. 90, 63-76

Simpson, E.,Henneberg, M., 2002. Variation in soft-tissue thicknesses on the human face and their relation to craniometric dimensions. Am J Phys Anthropol 118, 121-133

Stephan, C.N.,Simpson, E.K., 2008. Facial Soft Tissue Depths in Craniofacial Identification (Part I):An Analytical Review of the Published Adult Data. J. Forensic Sci. 53, 1257-1272

Szklarczyk, D., Gable, A.L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N.T., Morris, J.H., Bork, P., et al., 2019. STRING v11:protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607-D613

Tsagkrasoulis, D., Hysi, P., Spector, T.,Montana, G., 2017. Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping. Sci. Rep.-Uk. 7

Weinberg, S.M., Parsons, T.E., Marazita, M.L.,Maher, B.S., 2013. Heritability of Face Shape in Twins:A Preliminary Study using 3D Stereophotogrammetry and Geometric Morphometrics. Dent. 3000 1

White, J.D., Indencleef, K., Naqvi, S., Eller, R.J., Hoskens, H., Roosenboom, J., Lee, M.K., Li, J., Mohammed, J., Richmond, S., et al., 2021. Insights into the genetic architecture of the human face. Nat. Genet. 53, 45-53

Wu, W., Zhai, G., Xu, Z., Hou, B., Liu, D., Liu, T., Liu, W.,Ren, F., 2019. Whole-exome sequencing identified four loci influencing craniofacial morphology in northern Han Chinese. Hum. Genet. 138, 601-611

Xiong, Z., Dankova, G., Howe, L.J., Lee, M.K., Hysi, P.G., de Jong, M.A., Zhu, G., Adhikari, K., Li, D., Li, Y., et al., 2019. Novel genetic loci affecting facial shape variation in humans. Elife 8

Yun, H.S., Jang, T.J., Lee, S.M., Lee, S.H.,Seo, J.K., 2020. Learning-based local-to-global landmark annotation for automatic 3D cephalometry. Phys. Med. Biol. 65

Zakany, J., Kmita, M.,Duboule, D., 2004. A dual role for Hox genes in limb anterior-posterior asymmetry. Science 304, 1669-1672

Zhou, Y., Zhou, B., Pache, L., Chang, M., Khodabakhshi, A.H., Tanaseichuk, O., Benner, C.,Chanda, S.K., 2019. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1523

Zhuang, X., Arridge, S., Hawkes, D.J.,Ourselin, S., 2011. A nonrigid registration framework using spatially encoded mutual information and free-form deformations. IEEE Trans. Med. Imaging 30, 1819-1828

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