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 novel. 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 revealed 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 human face is complex and multipartite, and characterization of its genetic architecture remains challenging. Using a multivariate genome-wide association study (GWAS) meta-analysis of 8,246 European individuals, we identified 203 genome-wide significant signals (120 also study-wide significant) associated with normal-range facial variation. Follow-up analyses find that the regions surrounding these signals are enriched for enhancer activity in cranial neural crest cells and craniofacial tissues, several regions harbor multiple signals with associations to different facial phenotypes, and there is evidence for potential coordinated actions of variants. In sum, our analyses provide insights for understanding how complex morphological traits are shaped by both individual and coordinated genetic actions.

Three-dimensional (3D) surface imaging using stereophotogrammetry has become increasingly popular in clinical settings, offering advantages for surgical planning and outcome evaluation. The handheld Vectra H1 is a low-cost, highly portable system that offers several advantages over larger stationary cameras, but independent technical validation is currently lacking. In this study, 3D facial images of 26 adult participants were captured with the Vectra H1 system and the previously validated 3dMDface system. Using error magnitude statistics, 136 linear distances were compared between cameras. In addition, 3D facial surfaces from each system were registered, heat maps generated, and global root mean square (RMS) error calculated. The 136 distances were highly comparable across the two cameras, with an average technical error of measurement (TEM) value of 0.84mm (range 0.19-1.54mm). The average RMS value of the 26 surface-to-surface comparisons was 0.43mm (range 0.33-0.59mm). In each case, the vast majority of the facial surface differences were within a ±1mm threshold. Areas exceeding ±1mm were generally limited to facial regions containing hair or subject to facial microexpressions. These results indicate that 3D facial surface images acquired with the Vectra H1 system are sufficiently accurate for most clinical applications.

The human face is complex and multipartite, and characterization of its genetic architecture remains intriguingly challenging. Applying GWAS to multivariate shape 2 phenotypes, we identified 203 genomic regions associated with normal-range facial variation, 117 of which are novel. The associated regions are enriched for both genes relevant to 4 craniofacial and limb morphogenesis and enhancer activity in cranial neural crest cells and craniofacial tissues. Genetic variants grouped by their contribution to similar aspects of facial 6 variation show high within-group correlation of enhancer activity, and four SNP pairs display evidence of epistasis, indicating potentially coordinated actions of variants within the same cell 8 types or tissues. In sum, our analyses provide new insights for understanding how complex morphological traits are shaped by both individual and coordinated genetic actions. 10 Main Text: 12 "One of the major problems confronting modern biology is to understand how complex morphological structures arise during development and how they are altered during evolution""complicated developmental choreography" in which intrinsic genetic factors, epigenetic factors, and interactions between the two make up the progeny genotype, which engages with the 20 environment to ultimately produce a complex morphological trait, defined thus by its composition from a number of separate component parts 1 . We now understand that the intrinsic 22 genetic factors ultimately contributing to complex morphological traits consist not only of single 2 variants altering protein structure and/or function, but also non-coding variants and interactions 24 among variants, each affecting multiple tissues and developmental timepoints. This realization necessitates the development and utilization of methods capable of describing the genetic 26 architecture of complex morphological traits, which includes identifying the individual genetic variants contributing to morphological variation as well as their interactions 2,3 . 28 The human face is an exemplar complex morphological structure. It is a highly multipartite structure resulting from the intricate coordination of genetic, cellular, and 30 environmental factors 4-6 . Through prior genetic association studies of quantitative traits, 51 loci have been implicated in normal-range craniofacial morphology, and an additional 50 loci have 32 been associated with self-reported nose size or chin dimples in a large cohort study 7 (Table S1).However, as with all complex morphological traits, our ability to identify and describe the 34 genetic architecture of the face is limited by our ability to accurately characterize its phenotypic variation 4 , identify variants of both large and small effect 8 , and identify interactions between 36 variants. We previously described a novel data-driven approach to facial phenotyping, which facilitated the identification and replication of 15 loci involved in global-to-local variation in 38 facial morphology 9 . Here, we apply this phenotyping approach...

Purpose Here we aimed to identify a novel genetic cause of tooth agenesis (TA) and/or orofacial clefting (OFC) by combining whole exome sequencing (WES) and targeted re-sequencing in a large cohort of TA and OFC patients. Methods WES was performed in two unrelated patients, one with severe TA and OFC and another with severe TA only. After identifying deleterious mutations in a gene encoding the low density lipoprotein receptor-related protein 6 (LRP6), all its exons were re-sequenced with molecular inversion probes, in 67 patients with TA, 1,072 patients with OFC and in 706 controls. Results We identified a frameshift (c.4594delG, p.Cys1532fs) and a canonical splice site mutation (c.3398-2A>C, p.?) in LRP6 respectively in the patient with TA and OFC, and in the patient with severe TA only. The targeted re-sequencing showed significant enrichment of unique LRP6 variants in TA patients, but not in nonsyndromic OFC. From the 5 variants in patients with TA, 2 affect the canonical splice site and 3 were missense variants; all variants segregated with the dominant phenotype and in 1 case the missense mutation occurred de novo. Conclusion Mutations in LRP6 cause tooth agenesis in man.