Three-dimensional facial morphology in Cantu syndrome

Helen I. Roessler, Kathleen Shields, Dorothy K. Grange, Nine V. A. M. Knoers, Gijs van Haaften, Peter Hammond, Mieke M. van Haelst*

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    5 Citations (Scopus)
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    Cantú syndrome (CS) was first described in 1982, and is caused by pathogenic variants in ABCC9 and KCNJ8 encoding regulatory and pore forming subunits of ATP-sensitive potassium (KATP) channels, respectively. It is characterized by congenital hypertrichosis, osteochondrodysplasia, extensive cardiovascular abnormalities and distinctive facial anomalies including a broad nasal bridge, long philtrum, epicanthal folds, and prominent lips. Many genetic syndromes, such as CS, involve facial anomalies that serve as a significant clue in the initial identification of the respective disorder before clinical or molecular diagnosis are undertaken. However, an overwhelming number of CS patients receive misdiagnoses based on an evaluation of coarse facial features. By analyzing three-dimensional images of CS faces, we quantified facial dysmorphology in a cohort of both male and female CS patients with confirmed ABCC9 variants. Morphometric analysis of different regions of the face revealed gender-specific significant differences in face shape. Moreover, we show that 3D facial photographs can distinguish between CS and other genetic disorders with specific facial dysmorphologies that have been mistaken for CS-associated anomalies in the past, hence assisting in an earlier clinical and molecular diagnosis. This optimizes genetic counseling and reduces stress for patients and parents by avoiding unnecessary misdiagnosis.

    Original languageEnglish
    Pages (from-to)1041-1052
    Number of pages12
    JournalAmerican Journal of Medical Genetics. Part A
    Issue number5
    Publication statusPublished - 1-May-2020


    • 3D imaging
    • Cantu syndrome
    • dense surface model (DSM)
    • dysmorphology
    • facial phenotyping
    • principal component analysis (PCA)
    • KCNJ8

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