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Many genetic syndromes involve a facial gestalt that suggests a preliminary diagnosis to an experienced clinical geneticist even before a clinical examination and genotyping are undertaken. Previously, using visualization and pattern recognition, we showed that dense surface models (DSMs) of full face shape characterize facial dysmorphology in Noonan and in 22q11 deletion syndromes. In this much larger study of 696 individuals, we extend the use of DSMs of the full face to establish accurate discrimination between controls and individuals with Williams, Smith-Magenis, 22q11 deletion, or Noonan syndromes and between individuals with different syndromes in these groups. However, the full power of the DSM approach is demonstrated by the comparable discriminating abilities of localized facial features, such as periorbital, perinasal, and perioral patches, and the correlation of DSM-based predictions and molecular findings. This study demonstrates the potential of face shape models to assist clinical training through visualization, to support clinical diagnosis of affected individuals through pattern recognition, and to enable the objective comparison of individuals sharing other phenotypic or genotypic properties.

Original publication

DOI

10.1086/498396

Type

Journal article

Journal

Am J Hum Genet

Publication Date

12/2005

Volume

77

Pages

999 - 1010

Keywords

Adult, Alleles, Chromosomes, Human, Pair 22, Chromosomes, Human, Pair 7, European Continental Ancestry Group, Face, Female, Gene Deletion, Genetic Markers, Humans, Imaging, Three-Dimensional, In Situ Hybridization, Fluorescence, Linear Models, Male, Microsatellite Repeats, Models, Anatomic, Noonan Syndrome, Pattern Recognition, Automated, Polymorphism, Genetic