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J Med Genet. 2010 Dec;47(12):803-8. doi: 10.1136/jmg.2009.069617. Epub 2009 Sep 15.

Scalp fibroblasts have a shared expression profile in monogenic craniosynostosis.

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  • 1Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DS, UK.



Craniosynostosis can be caused by both genetic and environmental factors, the relative contributions of which vary between patients. Genetic testing identifies a pathogenic mutation or chromosomal abnormality in ∼ 21% of cases, but it is likely that further causative mutations remain to be discovered.


To identify a shared signature of genetically determined craniosynostosis by comparing the expression patterns in three monogenic syndromes with a control group of patients with non-syndromic sagittal synostosis.


Fibroblasts from 10 individuals each with Apert syndrome (FGFR2 substitution S252W), Muenke syndrome (FGFR3 substitution P250R), Saethre-Chotzen syndrome (various mutations in TWIST1) and non-syndromic sagittal synostosis (no mutation detected) were cultured. The relative expression of ∼ 47,000 transcripts was quantified on Affymetrix arrays.


435, 45 and 46 transcripts were identified in the Apert, Muenke and Saethre-Chotzen groups, respectively, that differed significantly from the controls. Forty-six of these transcripts were shared between two or more syndromes and, in all but one instance, showed the same direction of altered expression level compared with controls. Pathway analysis showed over-representation of the shared transcripts in core modules involving cell-to-cell communication and signal transduction. Individual samples from the Apert syndrome cases could be reliably distinguished from non-syndromic samples based on the gene expression profile, but this was not possible for samples from patients with Muenke and Saethre-Chotzen syndromes.


Common modules of altered gene expression shared by genetically distinct forms of craniosynostosis were identified. Although the expression profiles cannot currently be used to classify individual patients, this may be overcome by using more sensitive assays and sampling additional tissues.

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