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Related Experiment Videos

Phenotypic abnormalities: terminology and classification.

Johannes H M Merks1, Clara D M van Karnebeek, Hubert N Caron

  • 1Department of Pediatric Oncology/Emma Children's Hospital, Academic Medical Center, Amsterdam, The Netherlands. j.h.merks@amc.uva.nl

American Journal of Medical Genetics. Part A
|November 11, 2003
PubMed
Summary
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Clinical morphology aids in identifying genetic syndromes and candidate genes through careful patient evaluation. This study introduces a standardized classification system for physical anomalies to improve the assessment of developmental disturbances in various patient groups, including childhood cancer survivors.

Area of Science:

  • Medical genetics
  • Clinical dysmorphology
  • Developmental biology

Background:

  • Clinical morphology is crucial for identifying genetic syndromes and candidate genes.
  • Previous studies on anomalies in cancer patients lacked methods to assess biologic relevance or classify anomaly importance.
  • A lack of consensus on classifying anomalies hinders systematic evaluation of developmental disturbances.

Purpose of the Study:

  • To develop a uniform classification system for errors of morphogenesis detectable on surface examination.
  • To enhance uniformity in scoring and classifying physical findings and errors of morphogenesis.
  • To enable systematic evaluation of phenotypic anomaly patterns and determine the importance of symptoms in study populations.

Main Methods:

  • Proposed a classification system categorizing anomalies into common variants (>4% prevalence), minor anomalies (

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  • Piloted the classification list in a cohort of childhood cancer survivors to detect anomaly patterns related to specific tumor types.

    • Main Results:

    • The classification system provides a nomenclature for errors of morphogenesis and a uniform classification structure.
    • The system facilitates the assessment of developmental disturbances and the importance of symptoms in study populations.
    • Feasibility testing in childhood cancer survivors demonstrated the system's utility in detecting anomaly patterns.

    Conclusions:

    • The developed classification list enhances uniformity in assessing physical anomalies and their potential developmental origins.
    • This standardized approach aids in identifying patterns of anomalies and potential causative genes in diverse patient groups.
    • The system is valuable for research in general populations and for patients with suspected developmental anomalies, including cancer survivors.