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Related Experiment Videos

Anthropometric craniofacial pattern profiles in Down syndrome

J E Allanson1, P O'Hara, L G Farkas

  • 1Children's Hospital of Eastern Ontario, Ottawa, Canada.

American Journal of Medical Genetics
|October 1, 1993
PubMed
Summary
This summary is machine-generated.

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Anthropometric craniofacial measurements in Down syndrome (DS) reveal characteristic facial changes with age, including reduced ear length and altered maxillary-mandibular growth. These profiles accurately identify individuals with DS, aiding syndrome recognition.

Area of Science:

  • Medical Science
  • Genetics
  • Anthropology

Background:

  • Down syndrome (DS) is a genetic disorder associated with distinct craniofacial features.
  • Understanding craniofacial development in DS is crucial for diagnosis and management.
  • Previous studies have identified some craniofacial anomalies in DS, but detailed age-related changes require further investigation.

Purpose of the Study:

  • To characterize anthropometric craniofacial measurements in individuals with Down syndrome (DS) across a wide age range.
  • To identify specific craniofacial features and growth patterns associated with DS.
  • To evaluate the utility of craniofacial pattern profiles for DS identification.

Main Methods:

  • Collected 21 anthropometric craniofacial measurements from 199 individuals with DS (6 months to 61 years).

Related Experiment Videos

  • Compared measurements to age- and sex-matched normal standards to create Z score pattern profiles.
  • Employed stepwise forward discriminant function analysis to identify key classifying variables.
  • Main Results:

    • Confirmed brachycephaly (short head) and reduced ear length in individuals with DS.
    • Observed reduced maxillary growth relative to mandibular growth with increasing age, altering facial shape.
    • A subset of three variables (ear length, maxillary arc, upper facial depth) accurately classified over 99% of individuals.

    Conclusions:

    • Anthropometric craniofacial pattern profiles effectively define abnormal facial dimensions in DS and track age-related changes.
    • This technique demonstrates high accuracy in classifying individuals with and without DS (96.8% of DS subjects correctly classified).
    • The method shows promise for facilitating syndrome recognition, carrier identification, and inter-syndrome comparisons.