Seth M. Weinberg

Exome sequencing (ES) is now a relatively straightforward process to identify causal variants in Mendelian disorders. However, the same is not true for ES in families where the inheritance patterns are less clear, and a complex etiology is suspected. Orofacial clefts (OFCs) are highly heritable birth defects with both Mendelian and complex etiologies. The phenotypic spectrum of OFCs may include overt clefts and several subclinical phenotypes, such as discontinuities in the orbicularis oris muscle (OOM) in the upper lip, velopharyngeal insufficiency (VPI), microform clefts or bifid uvulas. We hypothesize that expanding the OFC phenotype to include these phenotypes can clarify inheritance patterns in multiplex families, making them appear more Mendelian. We performed exome sequencing to find rare, likely causal genetic variants in 31 multiplex OFC families, which included families with multiple individuals with OFCs and individuals with subclinical phenotypes. We identified likely causal variants in COL11A2 , IRF6 , SHROOM3, SMC3, TBX3 , and TP63 in six families . Although we did not find clear evidence supporting the subclinical phenotype hypothesis, our findings support a role for rare variants in the etiology of OFCs.

The effects of sex on human facial morphology have been widely documented. Because sexual dimorphism is relevant to a variety of scientific and applied disciplines, it is imperative to have a complete and accurate account of how and where male and female faces differ. We apply a comprehensive facial phenotyping strategy to a large set of existing 3D facial surface images. We investigate facial sexual dimorphism in terms of size, shape, and shape variance. We also assess the ability to correctly assign sex based on shape, both for the whole face and for subregions. We applied a predefined data‐driven segmentation to partition the 3D facial surfaces of 2446 adults into 63 hierarchically linked regions, ranging from global (whole face) to highly localized subparts. Each facial region was then analyzed with spatially dense geometric morphometrics. To describe the major modes of shape variation, principal components analysis was applied to the Procrustes aligned 3D points comprising each of the 63 facial regions. Both nonparametric and permutation‐based statistics were then used to quantify the facial size and shape differences and visualizations were generated. Males were significantly larger than females for all 63 facial regions. Statistically significant sex differences in shape were also seen in all regions and the effects tended to be more pronounced for the upper lip and forehead, with more subtle changes emerging as the facial regions became more granular. Males also showed greater levels of shape variance, with the largest effect observed for the central forehead. Classification accuracy was highest for the full face (97%), while most facial regions showed an accuracy of 75% or greater. In summary, sex differences in both size and shape were present across every part of the face. By breaking the face into subparts, some shape differences emerged that were not apparent when analyzing the face as a whole. The increase in facial shape variance suggests possible evolutionary origins and may offer insights for understanding congenital facial malformations. Our classification results indicate that a high degree of accuracy is possible with only parts of the face, which may have implications for biometrics applications.