Paper Title
Cluster Analysis of Facial Phenotypes in Autism Spectrum Disorders based on 3D Facial Models

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders with an estimated incidence of 1/59. Etiology of ASD has not been adequately explained; it is supposed to be a complex combination of environmental and genetic factors. Clinical signs and symptoms are very variable and involve intellectual disability of various degrees, epilepsy (including abnormal EEG) and hyperkinetic disorder. Endophenotyping in these patients is very challenging. Hence 3D analysis (“gestalt” analysis) of facial traits is a novel promising method. We analyzed a database containing a total of 106 3D facial scans of ASD patients of both sexes between 8-12 years of age. Scans were annotated with selected anthropometric landmarks and euclidean (linear) distances between all possible combinations of landmarks were calculated. Multiple cluster analyses of this data were carried out. Obtained data was correlated with clinical patient information. Female cases with ASD were analyzed for the first time in this manner. We disproved the original thesis, that ASD patients cluster separately from controls. We suspect that an imperfect exclusion process took place in the methodology of the original publication. As of yet we have not been able to run the analysis on geodesic distances, which may bring additional light into this issue. This analysis is planned in the near future. Keywords - Autism, Genetics, 3D Morphology, Facial Geometry, Anthropometry,