Journal of Autism and Developmental Disorders

, Volume 45, Issue 5, pp 1302–1317 | Cite as

Facial Structure Analysis Separates Autism Spectrum Disorders into Meaningful Clinical Subgroups

  • Tayo Obafemi-Ajayi
  • Judith H. Miles
  • T. Nicole Takahashi
  • Wenchuan Qi
  • Kristina Aldridge
  • Minqi Zhang
  • Shi-Qing Xin
  • Ying He
  • Ye DuanEmail author
Original Paper


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.


Autism Cluster analysis Language regression Facial phenotype Biomarker Outcome indicators 


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Tayo Obafemi-Ajayi
    • 1
    • 2
  • Judith H. Miles
    • 3
    • 4
  • T. Nicole Takahashi
    • 3
  • Wenchuan Qi
    • 2
  • Kristina Aldridge
    • 5
  • Minqi Zhang
    • 6
  • Shi-Qing Xin
    • 6
    • 7
  • Ying He
    • 6
  • Ye Duan
    • 2
    Email author
  1. 1.Applied Computational Intelligence Lab, Department of Electrical and Computer EngineeringMissouri University of Science and TechnologyRollaUSA
  2. 2.Department of Computer ScienceUniversity of MissouriColumbiaUSA
  3. 3.Thompson Center for Autism and Neurodevelopmental DisordersUniversity of MissouriColumbiaUSA
  4. 4.Department of Child HealthUniversity of Missouri School of MedicineColumbiaUSA
  5. 5.Department of Pathology and Anatomical SciencesUniversity of Missouri School of MedicineColumbiaUSA
  6. 6.School of Computer EngineeringNanyang Technological UniversitySingaporeSingapore
  7. 7.College of Information Science and EngineeringNingbo UniversityNingboChina

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