Craniofacial features of 3q29 deletion syndrome: application of next generation phenotyping technology.

Introduction3q29 deletion syndrome (3q29del) is a recurrent deletion syndrome associated with neuropsychiatric disorders and congenital anomalies. Dysmorphic facial features have been described but not systematically characterized. This study aims to detail the 3q29del craniofacial phenotype and use a machine learning approach to categorize individuals with 3q29del through analysis of 2D photos. MethodsDetailed dysmorphology exam and 2D facial photos were ascertained from 31 individuals with 3q29del. Photos were used to train the next generation phenotyping platform Face2Gene (FDNA, Inc, Boston, MA) to distinguish 3q29del cases from controls, using a proprietary algorithm. Area under the curve of receiver operating characteristic curves (AUC-ROC) were used to determine the capacity of Face2Gene to identify 3q29del cases against controls. ResultsIn this cohort, the most common observed craniofacial features were prominent forehead (48.4%), prominent nose tip (35.5%), and thin upper lip vermillion (25.8%). The FDNA technology showed an ability to distinguish cases from controls with an AUC-ROC value of 0.873 (p = 0.006). ConclusionThis study found a recognizable facial pattern in 3q29del, as observed by trained clinical geneticists and next generation phenotyping technology. These results expand the potential application of automated technology such as FDNA in identifying rare genetic syndromes, even when facial dysmorphology is subtle.