Scalp fibroblasts have a shared expression profile in monogenic craniosynostosis

Abstract

Background: 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.

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Figure 1

Cluster analysis of gene expression in craniosynostosis (CRS). The dendrogram shows the results of unsupervised clustering analysis of 10 samples each of Apert syndrome (AS) (AP_01–AP_10), Muenke syndrome (MS) (M_01–M_10), Saethre–Chotzen syndrome (SCS) (SCS_01–SCS_10), and 10 non-syndromic sagittal synostosis (NSS) controls (C_01–C_10), using information from all the probe sets of the Affymetrix U133 Plus 2.0 arrays.

Figure 2

Fibroblast expression signature distinguishes Apert syndrome (AS) samples from non-syndromic sagittal synostosis (NSS) controls. (A) Prediction Analysis for Microarrays (PAM) analysis. The upper panel shows the predictive power (measured by misclassification error on the y axis) of the full list of genes (extreme left on the x axis) to a single classifying gene (extreme right of the x axis). The best predictive power, hence smallest misclassification error, is achieved with the top 73 classifying genes (arrow). The lower panel shows the misclassification error for each diagnosis, with the NSS controls in red and AS cases in green. (B) Supervised clustering and heat map generated with the top 73 AS-classifying genes.

Figure 3

Comparison of syndromic craniosynostosis (CRS) expression profiles. A Venn diagram of the lists from the Statistical Analysis for Microarrays (SAM) analysis corresponding to the three conditions (Apert syndrome (AS), Muenke syndrome (MS) and Saethre–Chotzen syndrome (SCS)) is shown. Genes showing significant alterations in two or more conditions are identified individually; upregulated genes are shown in bold, and downregulated genes in normal type. A single gene (PDE4DIP, underlined) showed an inconsistent direction of change, with upregulation in MS and downregulation in AS.

Figure 4

Real-time PCR (RT-PCR) validation of the expression of HLA-DPA1, MMP1 and TGFBR2 genes in five further AS cases (P253R mutation) and five further NSS controls. The values presented are log-transformed and normalised to GAPDH control gene expression. All the data reached statistical significance (Student t test, p<0.05).