Abstract
Varied cluster analysis were applied to facial surface measurements from 62 prepubertal boys with essential autism to determine whether facial morphology constitutes viable biomarker for delineation of discrete Autism Spectrum Disorders (ASD) subgroups. Earlier study indicated utility of facial morphology for autism subgrouping (Aldridge et al. in Mol Autism 2(1):15, 2011). Geodesic distances between standardized facial landmarks were measured from three-dimensional stereo-photogrammetric images. Subjects were evaluated for autism-related symptoms, neurologic, cognitive, familial, and phenotypic variants. The most compact cluster is clinically characterized by severe ASD, significant cognitive impairment and language regression. This verifies utility of facially-based ASD subtypes and validates Aldridge et al.'s severe ASD subgroup, notwithstanding different techniques. It suggests that language regression may define a unique ASD subgroup with potential etiologic differences.
Recommended Citation
T. Obafemi-Ajayi et al., "Facial Structure Analysis Separates Autism Spectrum Disorders Into Meaningful Clinical Subgroups," Journal of Autism and Developmental Disorders, vol. 45, no. 5, pp. 1302 - 1317, Springer, May 2015.
The definitive version is available at https://doi.org/10.1007/s10803-014-2290-8
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Autism; Biomarker; Cluster analysis; Facial phenotype; Language regression; Outcome indicators
International Standard Serial Number (ISSN)
1573-3432; 0162-3257
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Springer, All rights reserved.
Publication Date
01 May 2015
PubMed ID
25351828
