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Three-dimensional facial morphology in Cantú syndrome
Helen I Roessler1, Kathleen Shields2, Dorothy K Grange2,3
1Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
American Journal of Medical Genetics. Part A
|February 27, 2020
Summary
Cantú syndrome (CS) facial features can be distinguished using 3D imaging, aiding in earlier diagnosis. This analysis reveals gender-specific facial shape differences in CS patients with ABCC9 variants.
Area of Science:
- Genetics
- Medical imaging
- Dysmorphology
Background:
- Cantú syndrome (CS) is a genetic disorder caused by variants in ABCC9 and KCNJ8 genes.
- CS presents with congenital hypertrichosis, skeletal abnormalities, cardiovascular issues, and distinctive facial anomalies.
- Facial features are crucial diagnostic clues, but misdiagnoses are common due to overlapping coarse facial features.
Purpose of the Study:
- To quantify facial dysmorphology in Cantú syndrome patients using 3D imaging.
- To identify gender-specific differences in facial shape within the CS cohort.
- To assess the utility of 3D facial analysis in differentiating CS from other genetic disorders with similar facial features.
Main Methods:
- Analysis of three-dimensional (3D) facial images from a cohort of CS patients with confirmed ABCC9 variants.
- Quantitative morphometric analysis of different facial regions.
- Comparison of facial morphology between CS patients and other genetic disorders.
Main Results:
- Significant gender-specific differences in face shape were identified in CS patients.
- 3D facial photographs effectively distinguished Cantú syndrome from other genetic disorders with overlapping facial anomalies.
- Quantified facial dysmorphology provides objective data for diagnosis.
Conclusions:
- 3D facial morphometric analysis is a valuable tool for the diagnosis of Cantú syndrome.
- This method can help prevent misdiagnoses, leading to improved genetic counseling and reduced patient/parental stress.
- Objective facial analysis aids in earlier and more accurate clinical and molecular diagnosis of CS.
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