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Facial Structure Analysis Separates Autism Spectrum Disorders into Meaningful Clinical Subgroups

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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.

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Author information

Author notes

  1. Tayo Obafemi-Ajayi

    Present address: Applied Computational Intelligence Lab, Department of Electrical and Computer Engineering, Missouri University of Science and Technology, 301 W. 16th St, Rolla, MO, 65409, USA

  2. Shi-Qing Xin

    Present address: College of Information Science and Engineering, Ningbo University, 818 Fenghua Road, Ningbo, Zhejiang, China

Authors and Affiliations

  1. Department of Computer Science, University of Missouri, 201 Engineering Building West, Columbia, MO, 65211, USA

    Tayo Obafemi-Ajayi, Wenchuan Qi & Ye Duan

  2. Thompson Center for Autism and Neurodevelopmental Disorders, University of Missouri, 205 Portland Street, Columbia, MO, 65211, USA

    Judith H. Miles & T. Nicole Takahashi

  3. Department of Child Health, University of Missouri School of Medicine, One Hospital Dr, N712, Columbia, MO, 65212, USA

    Judith H. Miles

  4. Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, One Hospital Dr, M309 Med Sci Bldg, Columbia, MO, 65212, USA

    Kristina Aldridge

  5. School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore

    Minqi Zhang, Shi-Qing Xin & Ying He

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  1. Tayo Obafemi-Ajayi
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Correspondence to Ye Duan.

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Obafemi-Ajayi, T., Miles, J.H., Takahashi, T.N. et al. Facial Structure Analysis Separates Autism Spectrum Disorders into Meaningful Clinical Subgroups. J Autism Dev Disord 45, 1302–1317 (2015). https://doi.org/10.1007/s10803-014-2290-8

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