Numerous lines of evidence indicate facial morphology has a strong genetic basis. However, relatively little is known about how specific genetic variants influence the size and shape of facial features in humans. A deeper understanding of the genetic basis of such traits may provide insights into the fundamental mechanisms of craniofacial morphogenesis, improve our knowledge of the complex relationship between genotype and phenotype in craniofacial syndromes and birth defects, and eventually provide a basis for predicting facial features for treatment planning in craniofacial surgery and orthodontics. This project has two major aims: (1) map genetic variants influencing normal human facial morphology; and (2) determine whether such variants play a role in nonsyndromic orofacial clefting. To accomplish the first aim, we will generate quantitative facial shape phenotypes by applying a novel morphometric approach to existing datasets with available 3D facial images and genome-wide markers (n=10,482). This novel phenotyping approach, within a multivariate GWAS framework, will allow us to model genetic effects on facial morphology at multiple levels of organization ? from highly localized to more global facial regions. We will begin to explore putative functionality by investigating the role of these variants in cranial neural crest cell regulation. Finally, by characterizing the relationships and interactions among associated variants, we will gain a better understanding of the genetic architecture of human facial variation. To accomplish the second aim, we will evaluate whether genetic variants associated with specific aspects of facial shape in our normal facial cohorts also contribute to the genetic etiology of nonsyndromic orofacial clefting, the most common craniofacial anomaly in humans. The aspects of shape we will focus on are based on prior evidence identifying certain facial features as predisposing factors to orofacial clefting (e.g., increased midfacial width in the unaffected parents of children with clefts). We will test these variants for association with orofacial clefting in an existing multiethnic cohort of nonsyndromic cleft cases and their unaffected first-degree relatives (n=9213). We will then determine the degree to which such variants modify and interact with previously identified cleft loci to influence phenotypic severity. By leveraging a large number of existing data resources and applying state-of-the-art advances in 3D phenotype-genotype modeling, the current proposal represents the most comprehensive effort to date to map the loci underlying human facial variation and an opportunity to gain important insights into the genetic etiology of a congenital malformation that impacts humans worldwide.
Despite the fact that the size and shape of our facial features is heritable, the specific genetic variants that influence normal facial morphology are largely unknown. Investigation into the genetic architecture of normal human facial variation may provide insights into the fundamental mechanisms of craniofacial morphogenesis, improve our understanding of the complex relationship between genotype and phenotype in craniofacial malformations, and eventually allow for the prediction of facial features for surgical and orthodontic treatment planning. The goals of this application are to identify genetic variants associated with facial shape in humans and to use this information to gain insights into the etiology of nonsyndromic clefting.
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| Roosenboom, Jasmien; Lee, Myoung Keun; Hecht, Jacqueline T et al. (2018) Mapping genetic variants for cranial vault shape in humans. PLoS One 13:e0196148 |
| Claes, Peter; Roosenboom, Jasmien; White, Julie D et al. (2018) Genome-wide mapping of global-to-local genetic effects on human facial shape. Nat Genet 50:414-423 |
| Hoskens, Hanne; Li, Jiarui; Indencleef, Karlijne et al. (2018) Spatially Dense 3D Facial Heritability and Modules of Co-heritability in a Father-Offspring Design. Front Genet 9:554 |
| Shaffer, John R; Li, Jinxi; Lee, Myoung Keun et al. (2017) Multiethnic GWAS Reveals Polygenic Architecture of Earlobe Attachment. Am J Hum Genet 101:913-924 |
