Differential Expression of Extracellular Matrix-Mediated
Pathways in Single-Suture Craniosynostosis
Brendan D. Stamper1*, Sarah S. Park1, Richard P. Beyer2, Theo K. Bammler2, Frederico M. Farin2, Brig
Mecham3, Michael L. Cunningham1,4
1Center for Tissue and Cell Sciences, Seattle Children’s Research Institute, Seattle, Washington, United States of America, 2Department of Environmental and
Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America, 3Sage Bionetworks, Seattle, Washington, United States of
America, 4Division of Craniofacial Medicine and the Department of Pediatrics, University of Washington, Seattle, Washington, United States of America
Craniosynostosis is a disease defined by premature fusion of one or more cranial sutures. The mechanistic pathology of
single-suture craniosynostosis is complex and while a number of genetic biomarkers and environmental predispositions
have been identified, in many cases the causes remain controversial and inconclusive. In this study, gene expression data
from 199 patients with isolated sagittal (n=100), unilateral coronal (n=50), and metopic (n=49) synostosis are compared
against both a control population (n=50), as well as each other. After controlling for variables contributing to potential bias,
FGF7, SFRP4, and VCAM1 emerged as genes associated with single-suture craniosynostosis due to their significantly large
changes in gene expression compared to the control population. Pathway analysis implicated focal adhesion and
extracellular matrix (ECM)-receptor interaction as differentially regulated gene networks when comparing all cases of single-
suture synostosis and controls. Lastly, overall gene expression was found to be highly conserved between coronal and
metopic cases, as evidenced by the fact that WNT2 and IGFBP2 were the only genes differentially regulated to a significantly
large extent in a direct comparison. The identification of genes and gene networks associated with Fgf/Igf/Wnt signaling
and ECM-mediated focal adhesion not only support the involvement of biomarkers previously reported to be related to
craniosynostosis, but also introduce novel transcripts and pathways that may play critical roles in its pathogenesis.
Citation: Stamper BD, Park SS, Beyer RP, Bammler TK, Farin FM, et al. (2011) Differential Expression of Extracellular Matrix-Mediated Pathways in Single-Suture
Craniosynostosis. PLoS ONE 6(10): e26557. doi:10.1371/journal.pone.0026557
Editor: Baochuan Lin, Naval Research Laboratory, United States of America
Received July 8, 2011; Accepted September 28, 2011; Published October 19, 2011
Copyright: ? 2011 Stamper et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the following National Institute of Health (NIH) grants: (NIH/NIDCR R01 DE018227) awarded to MLC, (NIH/NIEHS
P30ES07033), (NIH/NICHD P30HD02274). MLC also obtained support for this work from the Jean Renny Endowment for Craniofacial Research. The funders had no
role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
Craniosynostosis is the pathologic fusion of calvarial bones that
is associated with abnormal skull growth and increased intracra-
nial pressure. While the pathogenesis of single-suture craniosyn-
ostosis (which occurs in approximately 1/2500 live births) is poorly
understood, genetic causes are likely given a 7–10% recurrence
rate . However, recurrence rates based on pre-molecular
epidemiological data may be upwardly biased because of
contamination of nonsyndromic cases with individuals with single
gene disorders. The most common form of craniosynostosis
involves the fusion of a single suture (85–95%), but cases involving
multiple sutures are relatively common (5–15%) [2,3]. Approxi-
mately half of all single-suture craniosynostosis cases involve
premature fusion of the sagittal suture, whereas premature fusion
of the coronal and metopic sutures occurs in approximately 22%
and 15% of cases, respectively. Lambdoid craniosynostosis is very
rare, occurring in approximately 2% of all cases .
Craniosynostosis can be further categorized into syndromic and
non-syndromic forms. Mutations in a number of different genes
have been associated with syndromic craniosynostosis such as
FGFR1-3, TWIST1, EFNB1, FBN1, MSX2, RAB23, RECQL4, and
TGFBR1-2 . In fact, there are over one hundred well-
established syndromic forms of craniosynostosis with known
modes of inheritance, suggesting that genomic disposition plays
an important role in this disease . While multiple reports have
identified single gene mutations in nonsyndromic coronal
synostosis [6,7,8,9], in general, mutations associated with single-
suture synostosis remain elusive and rarely overlap with those
causing syndromic forms of the disease [4,8,10,11]. While this
evidence suggests a strong genetic component exists for all forms of
craniosynostosis, contributions from both genetic and environ-
mental factors likely play a role in premature suture closure for
non-syndromic forms of the disease. Results from a number of risk
association studies aimed at identifying environmental risk factors
related to craniosynostosis have been largely inconclusive ;
however, evidence for intrauterine head constraint [13,14,15],
maternal smoking [16,17], and fertility treatments  as
predisposing causes does exist.
The fact that a number of environmental and genetic risk
factors have been associated with developing craniosynostosis
suggests that there is no single gene, factor, or pathway responsible
for causing single-suture craniosynostosis. Rather, several inde-
pendent mechanisms likely lead to the occurrence of several
different forms of craniosynostosis, thus complicating the elucida-
tion of these mechanisms . Numerous transcriptomic studies
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have been performed to gain insight into the pathogenesis of
craniosynostosis, however the vast majority analyzed cases of
syndromic synostosis [20,21,22,23], or a combination of syndro-
mic and nonsyndromic cases [24,25]. While these studies have
provided great insight into the molecular mechanisms controlling
the premature fusion of calvarial sutures in syndromic craniosyn-
ostosis, more work is needed to assess gene expression changes in
nonsyndromic forms of this disease.
The transcriptomic study presented here is the largest of its
kind, and the first to analyze gene expression changes in calvaria
osteoblasts as they relate solely to nonsyndromic craniosynostosis.
A rich set of transcriptomic data from a panel of well-
characterized clinical samples was generated (199 synostosis cases
and 50 controls), from which potentially pathogenic changes in
gene expression among different forms of single-suture craniosyn-
ostosis were identified. In addition, subsequent pathway analysis
on the dataset suggested that transcriptomic regulation of genes
associated with extracellular matrix (ECM)-mediated focal adhe-
sion play an important role in differentiating patients with
craniosynostosis from unaffected individuals.
Comparison of suture-based gene expression patterns
compared to controls
To identify the set of genes that were significantly varying across
the sample population, nearly thirty thousand genes were ranked
based on their gene information content (GIC) scores, which was
defined as the percent variance explained by the first eigengene
obtained from a decomposition of the probe-level data for each
gene. In other words, high information content genes have
consistent probe level expression, meaning that multiple probes
within the same gene are changing in a uniform manner. The two
thousand genes with the highest GIC scores are listed in Table S1.
These genes were then analyzed by 2-dimensional hierarchical
clustering, evaluating gene expression patterns among different
cases of craniosynostosis compared to controls (Figure 1A). With
respect to genes with high GIC scores, the clustering dendrogram
is consistent with sagittal cases being distinct from the metopic and
coronal cases. Statistical analysis of the gene list revealed that
expression levels for 736 of the 2000 (36.8%) were considered
significant (p,0.05) when comparing synostosis and control cases
(Figure 1B). Again, sagittal cases were distinct from other cases
when looking at significant expression changes. The list of
significant gene expression changes with high information content
was further enriched to include only those changes in gene
expression considered to be both significant (p,0.05) and large
(|% change| .50) when comparing cases and controls. This
comparison identified 49 genes that satisfied these statistical
thresholds (Figure 1C). As with previous comparisons (non-
significant and significant only), sagittal cases were again distinct
from metopic and coronal cases with respect to large and
significant changes in gene expression. Interestingly, only the
expression of fibroblast growth factor 7 (FGF7), vascular cell
adhesion molecule 1 (VCAM1), and secreted frizzled-related
protein 4 (SFRP4) were considered to be significant and large in
all three cases of single-suture synostosis when compared to
controls (Table 1).
Comparison of significantly large changes in suture-
based gene expression compared to controls
Of the 49 gene expression changes considered to be significant
and large in at least one or more of the forms of single-suture
synostosis (Table S2), 36 were associated with coronal cases, 25
with metopic cases, and 14 with sagittal cases (Figure 2). To fully
investigate the relationship between the form of single-suture
synostosis and the expression of these genes, Venn diagrams were
constructed in order to identify gene sets that were either unique
or shared among the cases (Figure 3). Changes in the expression of
nineteen of these genes (Venn regions m1and m2) were consistent
among metopic and coronal cases comprising approximately 79%
(for metopic) and 54% (for coronal) of the expression changes
considered to be significantly large. Taken together, these results
highlight the fact that there are consistent hallmarks of gene
expression among osteoblasts derived from cases of synostosis,
especially among coronal and metopic cases; however each form
of the disease also possesses its own unique expression pattern.
Figure 1. Comparison of Gene Expression patterns between osteoblasts derived from cases of synostosis and control lines.
Heatmaps with 2-dimensional hierarchical clustering were generated for the 2000 genes with the highest correlation scores for probe expression (A),
and enriched subsets of this gene set where expression levels were considered significant (p,0.05) compared to controls (736 genes) (B), or both
significant (p,0.05) and large (|% change| .50) compared to controls (49 genes) (C).
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Direct comparison of gene expression
As gene expression profiles were highly conserved among
coronal and metopic cases compared to controls, direct compar-
isons between osteoblasts derived from these cases of synostosis
were investigated (Figure 4). Of the two thousand genes with the
highest GIC scores, only two (0.1%) were differentially expressed
between coronal and metopic sutures when comparing the cases
directly (Figure 4A, Table 2). WNT2 (wingless-type MMTV
integration site family member 2) expression was found to be
greater in coronal cases compared to metopic cases; however,
WNT2 expression was significantly higher in both compared to
controls (Table 2). In sagittal cases, WNT2 expression was
considered neither large (9% increase) nor significant (p.0.05)
compared to controls. Decreased IGFBP2 (insulin-like growth
factor binding protein 2) expression was specific to coronal cases as
no significant expression differences were observed between
metopic cases and control (Table 2).
When directly compared to sagittal cases, both coronal and
metopic cases show an increase in the number of genes
(Figure 4B and 4C). In fact, 22 of these differentially expressed
genes were identified in both the coronal versus sagittal and
metopic versus sagittal comparisons (Table 3). Furthermore, this
subset of genes represents 34% of the total genes in the coronal
versus sagittal comparison and 81% of total genes in the metopic
versus sagittal comparison. Again, these results highlight highly
conserved gene expression patterns in coronal and metopic cases,
significant and large extent
not only in comparisons to control samples, but also against
sagittal craniosynostosis cases directly.
KEGG pathway analysis
Prior analysis of the dataset investigated how similar gene
expression patterns were among osteoblasts derived from cases of
synostosis, and identified a number of potential gene targets.
However, how these changes in expression could affect biological
systems was not addressed. To this end, the two thousand genes
with the highest GIC scores were uploaded into DAVID in order
to identify basic biological pathways associated with genes in our
dataset that had consistent changes in expression at the probe
level. Using this gene list, focal adhesion and ECM-receptor
interaction were the two most significantly implicated pathways
(Table S3). In addition, the TGF-beta signaling pathway,
regulation of actin cytoskeleton, cell adhesion molecules (CAMs),
and gap junction were also identified as significantly enriched
pathways (p,0.01). Given that ECM-receptor interactions play a
critical role in focal adhesion, genes related to ECM-mediated
focal adhesion are of particular interest as potential transcriptomic
markers related to craniosynostosis. ECM-mediated focal adhesion
is a highly complex interplay between cells and incorporates over
fifty known factors , therefore only those found to be
differentially regulated between synostosis cases and controls are
represented in Figure 5. This modified KEGG pathway for ECM-
mediated focal adhesion includes the 25 genes associated with
focal adhesion, and 19 genes associated with ECM-receptor
Table 1. Gene expression consistent in osteoblasts derived from cases of synostosis compared to control lines.
log2 fold change (% change)
FGF7 1.01 (101)0.91 (88)0.91 (88) 0.89 (85)
VCAM10.93 (91)0.72 (65) 1.04 (106)0.75 (68)
SFRP4 1.08 (111)0.76 (69) 0.66 (58)0.66 (58)
Figure 2. MA-plots highlighting differential gene expression between osteoblasts derived from cases of synostosis and control
lines. Genes whose expression was considered to be significant (p,0.05) and large (|% change| .50) are represented by a red ‘‘X’’, whereas genes
whose expression did not meet threshold values are represented by black dots. Comparisons were made between coronal cases and control
populations (A), metopic cases and control populations (B), and sagittal cases and control populations (C).
Transcriptomic Profiling in Craniosynostosis
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interactions, that underwent significant changes in expression
(p,0.05) when comparing cases and controls. Expression data for
these genes can be found in Table S4.
Transcriptome comparisons among different forms of
The existing literature suggests that there is no single pathway
that causes craniosynostosis; rather, several independent mecha-
nisms likely lead to craniosynostotic endpoints. While genetic and
environmental factors have been implicated in craniosynostosis,
the goal of this manuscript was to identify key transcripts
associated with single-suture craniosynostosis. While the expres-
sion for many genes with high GIC scores changed unilaterally,
the clustering dendrograms suggested that sagittal cases were
distinct from metopic and coronal cases (Figure 1). The high
degree of correlation between coronal and metopic gene
expression is clearly visualized by a Venn diagram including the
fifty gene expression changes considered significantly large
Figure 3. Venn diagram highlighting unique or shared gene sets among different forms of single-suture craniosynostosis. Venn
region m1 contains genes shared among all three cases of single-suture synostosis, genes shared between two cases are contained in Venn regions
m2, m3, and m4, and genes unique to a specific case are contained in Venn regions m5 (coronal), m6 (metopic), and m7 (sagittal).
Figure 4. MA plots highlighting differential gene expression by directly comparing osteoblasts derived from cases of synostosis.
Genes whose expression was considered to be significant (p,0.05) and large (|% change| .50) are represented by a red ‘‘X’’, whereas genes whose
expression did not meet threshold values are represented by black dots. Comparisons were made between coronal and metopic cases (A), coronal
and sagittal cases (B), and metopic and sagittal cases (C).
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(Figure 3). This diagram highlights the overlap in the expression of
nineteen genes shared among coronal and metopic cases (Figure 3,
Venn regions m1and m2). Perhaps coronal and metopic synostosis
share very similar gene expression profiles because these forms of
single-suture craniosynostosis are rarer than sagittal synostosis and
have fewer root causes. In contrast, sagittal craniosynostosis cases
may appear more divergent because there are more root causes,
which may or may not be related to its higher incidence in the
general population compared to other forms of the disease. It is
also possible that differences in the embryonic origin of the
calvaria may explain some of the changes in gene expression that
were observed, as the frontal and parietal bones are derived from
neural crest and paraxial mesoderm, respectively [25,27].
FGF7 upregulation in craniosynostosis cases
Even though gene expression in sagittal cases appeared
divergent from that of coronal and metopic cases, changes in the
expression of three genes were found to be significant and large in
all osteoblasts derived from cases of synostosis, FGF7, VCAM1, and
SFRP4 (Table 1). Initially, the identification of FGF7 was most
striking, since gain of function mutations in FGF-receptors
(FGFRs) cause a number of craniosynostosis syndromes, including
Apert, Crouzon, Muenke, and Pfeiffer syndromes [3,28]. FGF7 is
expressed in loose mesenchyme surrounding the mesenchymal
condensation  and preferentially activates FGFR2b .
However, the S252W and P253R mutations in FGFR2 found in
Apert’s syndrome allow FGF7-mediated FGFR2c activation
[3,31]. Therefore, upregulation of signaling factors like FGF7
during mesenchymal condensation may lead to inappropriate
ligand-receptor binding, increased mitogenic activity, and thus
contribute to skeletal abnormalities related to craniosynostosis.
WNT2/SFRP4 upregulation in craniosynostosis cases
Like FGF7, SFRP4 was identified as a significantly upregulated
gene in all osteoblasts derived from cases of synostosis (Table 1).
SFRP4 has been shown to antagonize Wnt activation 
supporting previous reports that Wnt signaling plays a role in
the pathogenesis of craniosynostosis [33,34,35,36]. Furthermore,
when a direct comparison between coronal and metopic cases was
performed, WNT2 and IGFBP2 were the only two genes out of
over thirty thousand found to be differentially expressed to a
significantly large extent (Figure 4A). The fact that genes
associated with Wnt signaling (WNT2 and SFRP4) were identified
in these experiments is not surprising due to the fact that Wnt
signaling has been implicated not only in genetic disease states
related to bone, but also in bone and craniofacial development
[37,38,39,40,41]. In metopic and coronal cases, concurrent SFRP4
and WNT2 upregulation may appear counter-intuitive considering
SFRP4 has been shown to antagonize Wnt activation [32,42,43].
One possible explanation for this observation is that upregulation
of Wnt repressors like SFRP4, is a counter-regulatory response to
increased WNT2 expression or vice versa. In fact, simultaneous
upregulation in the expression of WNT2 and SFRP4 has been
previously reported in mouse skin and skeletal muscle . Also, a
recent microarray study comparing osteoblast expression from
wild-type and Apert syndrome fetuses identified concurrent WNT2
and SFRP1 upregulation in the tissues derived from syndromic
craniosynostosis cases . Another possible explanation for this
scenario is the fact that WNT2 has been shown to act via
noncanonical pathways [45,46], whereas SFRP4 has been shown
to inhibit canonical Wnt signaling in bone . Based on the
complexity of Wnt signaling and potential complications due to
tissue-specific functions of specific Wnt isoforms, future studies
focusing on the relationship between WNT2 and SFRP4 need to be
performed in order to elucidate whether concurrent upregulation
of these two genes in metopic and coronal cases is related to a
compensatory cellular response, canonical/noncanonical Wnt
signaling, or crosstalk with unidentified signaling cascades.
Interplay between Fgf and Wnt signaling
The fact that transcripts associated with Fgf and Wnt signaling
were identified as highly differentially regulated in synostosis cases
compared to controls, suggests that investigating potential crosstalk
mechanisms between these pathways may identify key aspects
relating to the pathogenesis of craniosynostosis. Both Fgf and Wnt
signaling have been implicated in the determination of mesen-
chymal cell fate and ossification mechanisms [28,48,49,50]. With
Table 2. Genes differentially expressed to a significant extent
when comparing coronal and metopic cases.
log2 fold change (% change)
Coronal_control 1.17 (125)
Metopic_control0.44 (36) 0.07 (5)*
Coronal_sagittal 1.05 (107)
Table 3. Differential gene expression consistent among
coronal and metopic cases compared to sagittal cases.
log2 fold change (% change)
ALX11.67 (218) 1.65 (214)
HAS2 0.96 (95)0.90 (87)
SLC14A10.85 (80)1.23 (135)
CHI3L10.75 (68) 0.76 (69)
KCNK2 0.75 (68)0.67 (59)
CLDN110.61 (53) 0.60 (52)
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respect to Wnt signaling, specificity with respect to canonical and
non-canonical pathways is critical, as canonical Wnt signaling
appears to repress chondrogenesis, whereas non-canonical Wnt-
signaling may promote chondrogenesis via inhibition of canonical
pathways . Whether Wnt-mediated chondrogenesis plays a
critical role in craniosynostosis is unclear. There is evidence that
repression of canonical Wnt signaling prevents premature suture
closure [34,36], however, results from a recent study suggests the
interplay between upstream canonical Wnt activity and down-
stream Fgf signaling is more critical . While signaling
mechanisms related to calvarial development and suture mainte-
nance is highly complex, it is evident that crosstalk between Wnt
and Fgf signaling pathways plays a key role in mesenchymal cell
fate as it relates to premature suture closure.
The role of ECM-mediated focal adhesion in
While the identification of individual genes as potential
biomarkers for craniosynostosis is useful, it is also important to
discover potential network biomarkers for the disease in addition to
individual transcripts like FGF7, SFRP4, and WNT2. To this end,
pathway analysis was performed to elucidate gene sets in which
individual gene expression changes may be smaller in magnitude,
however, en masse these genes may heavily implicate specific
pathways. When the list consisting of genes with high GIC scores
was interrogated using DAVID, two pathways were significantly
implicated to a greater degree than all the rest, focal adhesion and
ECM-receptor interactions (Table S3). During embryonic develop-
ment, variations in ECM macromolecule composition influences
bone tissue differentiation, so the identification of ECM-mediated
focal adhesion as a potential network biomarker for non-syndromic
single-suture craniosynostosis is of interest.
Despite some controversy, perturbations in ECM deposition
and regulation have been associated with Apert syndrome
[21,52,53,54]. In three of these studies, [52,53,54] upregulation
of ECM components and an increase in matrix mineralization was
observed in Apert models, whereas the majority of genes related to
cell adhesion and ECM composition was found to be downreg-
ulated in the fourth study . In our study, gene expression
related to ECM-mediated focal adhesion was mixed, with both up
and downregulation of specific ECM components occurring
(Figure 5). Although it is difficult to compare single-suture
craniosynostosis with syndromic forms of the disease, some of
the gene expression changes observed in this study have also been
seen in transcriptomic comparisons using tissues from syndromic
samples. Most interesting is the fact that one study observed
general downregulation of alpha integrin subunits (ITGAs) in
syndromic craniosynostosis, except for ITGA11 ; exactly what
was observed in this study (Figure 5). In another study comparing
differential expression during suture fusion from a mix of
syndromic and nonsyndromic craniosynostosis cases, THBS2 and
collagen types 2, 3, 4, 6, 8, 10 and 11 were found to be
upregulated in unfused sutures . Upregulation THBS2 and
collagen types 6 and 11 were observed in this study as well,
alluding to the fact that cartilage-specific gene expression and
perturbations to ECM-mediated processes are involved in suture
morphogenesis and a common feature in all forms of craniosyn-
Finally, identification of ECM-mediated focal adhesion as a
candidate network biomarker also substantiates the identification
of VCAM1 and IGFBP2 as potential individual gene biomarkers for
craniosynostosis. Vascular invasion has been characterized as an
important step in endochondral ossification  and this
mechanism of bone formation has been shown to result in
premature suture closure . This suggests that perturbations to
calvarial vascularization may lead to the disease state. The
identification vascular-related transcripts like VCAM1 (Table 1)
and FLT1 (VEGFR1, vascular endothelial growth factor receptor 1)
(Figure 5, Table S4) as differentially regulated (p,0.05) between
Figure 5. Differential expression of genes related to extracellular matrix-mediated focal adhesion in synostosis cases. Changes in
gene expression that were robustly expressed across the population of samples were uploaded into DAVID to identify enriched KEGG pathways
potentially affected in craniosynostosis. Genes with significant changes in expression between cases and controls that were related to either focal
adhesion or ECM-receptor interactions are mapped in this modified KEGG pathway. Differentially upregulated genes are boxed in red, differentially
downregulated genes are boxed in blue, and when up- and downregulated isoforms of the same gene family were observed, mixed expression was
assigned (boxed in gray).
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all single-suture synostosis cases and controls, suggests that
alterations to vascular components related to ECM-cell interac-
tions may be critical to premature suture closure mechanisms.
FLT1 is a receptor tyrosine kinase (RTK) that plays a key role in
focal adhesion-mediated vascular development (Figure 5). Fur-
thermore, mutations in IGF1R (insulin-like growth factor 1
receptor), another focal adhesion-related RTK, have been
identified as potential causes of single-suture craniosynostosis
. Insulin-like growth factor 1 (IGF1), a high affinity ligand for
IGF1R, was found to be upregulated in all osteoblasts derived
from cases of synostosis, albeit only to a significant extent in
coronal cases (Figure 5, Table S4). IGFBP2, which was found to be
downregulated in coronal cases compared to all other treatment
conditions (Table 2), is capable of binding to and inhibiting IGF
activity. [57,58,59]. Therefore, RTK-mediated alterations in focal
adhesion, such as IGF signaling (IGF1, IGFBP2), vascular invasion
(VCAM1, FLT1), or other RTK cascades, should be considered
potential candidate biomarkers for single-suture craniosynostosis.
This transcriptomic study has identified a number of potential
transcripts and one network biomarker related to craniosynostosis
from a rich set of whole genome gene expression data from
calvarial osteoblasts derived from a large panel of clinical samples.
The results from this study not only identified FGF7, SFRP4, and
VCAM1 as novel genetic candidates for the cause of single-suture
craniosynostosis like, but also confirmed the involvement of ECM-
mediated focal adhesion and Ffg/Wnt/Igf signaling pathways that
may contribute its pathogenesis. Furthermore, analysis of
transcriptome changes suggest that while the expression of certain
genes are consistent among all cases of craniosynostosis, expression
patterns for coronal and metopic synostosis are quite similar,
whereas gene expression in sagittal cases is more divergent. Future
investigations into the regulation of these individual transcripts
and gene networks related to the various forms of single-suture
craniosynostosis must account for the fact that the mechanistic
pathology of this disease is highly complex, likely resulting from a
wide array of root causes, both genetic and environmental.
Materials and Methods
Written informed consent was obtained from all participants
with single-suture craniosynostosis, whereas a waiver of consent
was obtained from the Seattle Children’s Hospital institutional
review board (IRB) for the anonymous control samples used in this
study. This study is HIPAA compliant, and we obtained
independent prospective IRB approval from each participating
center, including Seattle Children’s Hospital, Northwestern
University in Chicago, Children’s Heath Care of Atlanta, and
St. Louis Children’s Hospital.
Participants were enrolled as described previously in a
prospective, four-center investigation of neurodevelopment among
children with single-suture craniosynostosis . Infants were
referred to the study at the time of diagnosis by their treating
surgeon or pediatrician and were eligible if, at the time of
enrollment, they had isolated sagittal, unilateral coronal, metopic,
or unilateral lambdoid synostosis confirmed by CT scan. CT scans
were performed at each participating center, and de-identified
data were sent to Seattle Children’s Hospital for diagnosis
confirmation. Enrolled cases in the overall study were 84% of
those eligible, with distance or time constraints being the major
reason for nonparticipation. Lambdoid synostosis cases were
excluded from the present study due to insufficient numbers.
Exclusion criteria included the presence of major medical or
neurological conditions (e.g., cardiac defects, seizure disorders,
cerebral palsy, significant health conditions requiring surgical
correction, etc.); presence of three or more minor extra-cranial
malformations ; or presence of other major malformations.
Demographic data for the dataset are listed in Table 4.
Osteoblast expansion and culture
Calvaria samples from craniosynostosis cases were obtained
from discarded tissues during surgical reconstructive procedures,
whereas control calvaria samples were obtained from discarded
tissues from anonymous surgical or autopsy specimens. Harvested
calvaria samples were then washed with Waymouth’s media
(Sigma W1625 lot 097K8303) and cleaned of all soft tissue.
Calvarial were then sliced into thin 3–5mm diameter pieces and
placed in 12-well plates (2 pieces per well) containing 2 mL of
Waymouth’s media supplemented with 2X antibiotic (100X Pen/
Strep/Fungizone, Hyclone SV30079.01, lot JUA33955) and 10%
FBS (Hyclone SH30070.03, lot ATK33398). Upon reaching
confluence, the contents of each 12-well place were trypsinized
using 0.05% Trypsin (Hyclone SH30236.02, lot J090511) and
passaged into T75 flasks. Again, cells were grown to confluence
and passaged into cryogenic vials containing freezing media
consisting of 90% fetal bovine serum and 10% DMSO and placed
in a liquid nitrogen storage tank. Once ready to use, each
osteoblast line was thawed and grown in T25 flasks containing
Waymouth’s media supplemented with 2X antibiotic (100X Pen/
Strep/Fungizone) and 10% FBS. Subsets of the 249 cell lines
included 50 controls and 100 sagittal, 50 coronal, and 49 metopic
cases with craniosynostosis. Upon reaching 75% confluence, cells
were trypsinized using 0.05% Trypsin, counted and passaged at a
cell density of 175,000 cells per 25cm2. All cells were cultured at
37uC, 5% CO2, and 99% humidity. All cell lines were
characterized as osteoblasts by alkaline phosphatase staining in
12-well plates. Briefly, one BCIP/NBT tablet (Sigma B5655) was
dissolved in 10 mL deionized water, and 500 mL of this solution
was added for 30 minutes to each cell line. Representative staining
of osteoblasts is shown in Figure S1.
Table 4. Demographic information describing case and
n Average age (mo) Age range (mo)
Control 5031 1–120
Coronal 50 114–24
Metopic 499 3–19
Sagittal 1008 2–28
Transcriptomic Profiling in Craniosynostosis
PLoS ONE | www.plosone.org7 October 2011 | Volume 6 | Issue 10 | e26557
Cell harvest and RNA isolation
Following the plating of 175,000 cells per 25cm2, each
osteoblast cell line was once again grown to 75% confluence,
photographed for quality control purposes, washed twice with 1X
PBS, and trypsinized. An equal volume of media containing FBS
was added after trypsin exposure, and cells were centrifuged twice
at 200 x g for 10 minutes at 4uC in nuclease free 15ml conical
tubes (Corning 430791). Between centrifugation steps, cells were
washed once with 1X PBS. Cell pellets were then kept on ice until
RNA extraction. For RNA extraction, Roche High Pure miRNA
Isolation Kit was used with accordance to the manufacturer’s
protocol (Roche 050080576001). RNA was stored immediately in
280uC and submitted for microarray processing on dry ice.
RNA integrity was assessed using the Agilent 2100 Bioanalyzer,
and only samples passing quality control were analyzed for
transcriptomic changes using Affymetrix Human Gene 1.0 ST
was processed and analyzed with Bioconductor  and normalized
with the RMA method as implemented in the Bioconductor affy
package [63,64,65]. Microarray quality control metrics include the
manufacturer’s recommended guidelines: (1) visual inspection of
probe array images, (2) proper ranking of hybridization and Poly-A
controls, and (3) area under the curve values for a receiver operating
characteristic plot comparing the positive control and negative
control signal values. Other microarray quality control metrics from
the Bioconductor affyPLM package [63,65] were used, including the
relative log expression (RLE) values, used to see if expression values
are shifted or spread out, and the normalized unscaled standard
errors (NUSE), used to see if the variability of genes across arrays is
too large. To identify a set of genes whose expression levels vary
significantly across the population, singular value decomposition
(SVD) of the normalized data for each probe set was performed and
the percent variance explained by the 1stsingular value was
investigated. This value is referred to as the Gene Information
Content (GIC). A cutoff for significant GIC scores was defined by
permuting the probe-to-probe set map and calculating the percent
variance explained for each permuted probe set. This was repeated
one thousand times and the cutoff was defined as the 99thpercentile
of the permuted statistics. Furthermore, any probe set whose
observed GIC was less than this value was removed from
downstream analyses. All microarray data are MIAME compliant
and the raw dataset has been deposited in the MIAME compliant
Characterization of KGFLP1 expression
Upregulation of keratinocyte growth factor-like protein 1
(KGFLP1) was identified as significant and large in all three cases
of single-suture synostosis. KGFLP1 has been characterized as the
likely product of a pseudogene with high sequence homology to
the C-terminus region of FGF7 (UniProtKB: Q2TVT4). Because
FGF7 and KGFLP1 share a high degree of nucleotide sequence
identity and several probes that comprise the probe sets
corresponding to these transcripts can cross-hybridize, the
microarray data was also normalized at the individual probe level
and summarized at the exon level using Affymetrix Expression
Console software (http://www.affymetrix.com). This approach
allowed us to assess the fluorescent signal associated with probes
that do not cross-hybridize. For these results it was determined
that FGF7 was in fact cross-hybridizing with the 39 end probes of
KGFLP1, and that all probes specific to KGFLP1 contained in the
59 end were not differentially expressed.
DAVID pathway analysis
The initial step in this process was to identify genes that were
robustly expressed across the population of samples, which
generated a list of two thousand genes ranked by gene information
content (GIC) score (Table S1). (GIC) was defined as the percent
variance explained by the first eigengene obtained from a
decomposition of the probe-level data for each gene. Genes with
high GIC scores were uploaded to the online bioinformatics
database, DAVID (Database for Annotation, Visualization and
Integrated Discovery, http://david.abcc.ncifcrf.gov/) [66,67].
Using OFFICAL_GENE_SYMBOL as the identifier and Homo
sapiens as the background, the functional annotation tool was
utilized to identify pathways heavily implicated in regards to the
From the normalized data, genes with significant evidence for
differential expression were identified using the limma package
 in Bioconductor. A mixed effects model was used to
investigate the craniosynostosis phenotype while adjusting for
age and gender. A blocking variable, microarray processing date,
was included as a random effect. P-values were calculated with a
modified t-test in conjunction with an empirical Bayes method to
moderate the standard errors of the estimated log-fold changes. P-
values were adjusted for multiplicity using Bioconductor’s
implementation of the Benjamini-Hochberg method . The
Benjamini-Hochberg method is widely used to calculate false
discovery rates for microarray data. Thus, it allows for selecting
statistically significant genes while controlling the estimated false
Representative alkaline phosphatase staining of primary osteoblast
Characterization of primary osteoblast lines.
Top 2000 genes with high information content.
significant and large in at least one form of single-suture
craniosynostosis compared to controls.
Changes in gene expression considered to be
associated with craniosynostosis-related gene expres-
Identification of significant KEGG pathways
ECM-mediated focal adhesion with significant changes
in expression between cases and controls.
Genes identified in the dataset related to
We wish to thank Linda Peters for her assistance in the collection of
samples used for tissue culture and RNA isolation.
Conceived and designed the experiments: BDS MLC. Performed the
experiments: BDS SSP FMF BM. Analyzed the data: BDS RPB TKB BM
MLC. Contributed reagents/materials/analysis tools: BDS RPB MLC.
Wrote the paper: BDS MLC.
Transcriptomic Profiling in Craniosynostosis
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