Next Article in Journal
A Comprehensive Overview of Baboon Phylogenetic History
Previous Article in Journal
Fate Decisions of Chicken Primordial Germ Cells (PGCs): Development, Integrity, Sex Determination, and Self-Renewal Mechanisms
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 14
Issue 3
10.3390/genes14030615
genes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Review of Recurrently Mutated Genes in Craniosynostosis Supports Expansion of Diagnostic Gene Panels

by
Rebecca S. Tooze
1,
Eduardo Calpena
1,
Astrid Weber
2,
Louise C. Wilson
3,
Stephen R. F. Twigg
1,*,† and
Andrew O. M. Wilkie
1,†
1
Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
2
Liverpool Centre for Genomic Medicine, Liverpool Women’s NHS Foundation Trust, Liverpool L8 7SS, UK
3
North East Thames Regional Genetics Service, Great Ormond Street Hospital for Children NHS Foundation Trust, London WC1N 3JH, UK
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Genes 2023, 14(3), 615; https://doi.org/10.3390/genes14030615
Submission received: 29 January 2023 / Revised: 17 February 2023 / Accepted: 23 February 2023 / Published: 28 February 2023
(This article belongs to the Section Genetic Diagnosis)
Versions Notes

Abstract

:
Craniosynostosis, the premature fusion of the cranial sutures, affects ~1 in 2000 children. Although many patients with a genetically determined cause harbor a variant in one of just seven genes or have a chromosomal abnormality, over 60 genes are known to be recurrently mutated, thus comprising a long tail of rarer diagnoses. Genome sequencing for the diagnosis of rare diseases is increasingly used in clinical settings, but analysis of the data is labor intensive and involves a trade-off between achieving high sensitivity or high precision. PanelApp, a crowd-sourced disease-focused set of gene panels, was designed to enable prioritization of variants in known disease genes for a given pathology, allowing enhanced identification of true-positives. For heterogeneous disorders like craniosynostosis, these panels must be regularly updated to ensure that diagnoses are not being missed. We provide a systematic review of genetic literature on craniosynostosis over the last 5 years, including additional results from resequencing a 42-gene panel in 617 affected individuals. We identify 16 genes (representing a 25% uplift) that should be added to the list of bona fide craniosynostosis disease genes and discuss the insights that these new genes provide into pathophysiological mechanisms of craniosynostosis.

1. Introduction

Craniosynostosis, the premature fusion of one or more cranial sutures of the skull, is a clinically and genetically heterogeneous congenital anomaly, affecting approximately 1 in 2000 live births [1,2]. Despite being one of the most prevalent craniofacial abnormalities (second to cleft lip and/or cleft palate), the variability in its causes and presentation can make identifying a genetic diagnosis extremely challenging. Monogenic, polygenic [3,4], chromosomal, and environmental [5] factors have all been identified as likely causes of craniosynostosis, with a burden of over 20% of the cases originating from monogenic causes alone [6]. Although a majority of diagnoses are attributable to variants in just seven genes (EFNB1, ERF, FGFR2, FGFR3, SMAD6, TCF12 and TWIST1) [6,7,8], over 60 genes are known to be recurrently mutated in craniosynostosis more rarely [9,10]. For example, in an Oxford survey of 666 individuals with craniosynostosis, pathogenic variants were identified in 20 more rarely mutated genes in 23/666 individuals (3.5%) [6]. The observation of a long tail of rarer disease-causing variants was supported by a recent exome sequencing study of patients in Norway [1]. The identification of such rare causative variants is inevitably challenging in a clinical diagnostic setting, where the need for high sensitivity (recall), which minimizes false negative calls but involves intensive effort, has to be balanced against the need for high precision (positive predictive value), which minimizes false positive calls [11]. The use of diagnostic gene panels has been adopted to address this problem.
A test case is provided by the UK’s 100,000 Genomes Project (100 kGP), delivered by Genomics England Limited (GE) between 2014 and 2019 [12]. This initiative aimed to facilitate whole genome sequencing (WGS) for 100,000 National Health Service (NHS) patients or relatives with rare diseases or cancer, with the primary aim being to return information to participants on variants with sufficient evidence for diagnostic reporting related to their primary condition [12]. To facilitate this, GE curated PanelApp, a publicly available resource containing crowdsourced and disease-focused gene panels for all rare disease groupings within the 100 kGP (https://panelapp.genomicsengland.co.uk/; accessed on 12 December 2022) [13]. Genes on each panel are traffic-light coded based on the level of confidence for diagnostic reporting in a given rare disease. Green genes are those in which there are plausible disease-causing variants (de novo or rare variants that are fully-penetrant) that affect a functional region of the gene (open reading frame for protein-coding genes) and have been identified in three or more unrelated families with a specific rare disease, or within two or more unrelated families with strong additional functional data. Full criteria for categorization of Green panel genes are provided in Table S1. Scrutiny of variants identified in Green genes aids prioritization of likely pathogenic variants and decreases the number candidates that diagnostic laboratories are required to screen. Genes that do not meet these criteria are listed as Amber or Red, corresponding to moderate or insufficient evidence for gene-disease association, respectively [13].
While the use of panels greatly facilities workflow through complex genomic datasets, their full utility is critically dependent on regular updating to take account of recent research findings, in order to maximize diagnostic sensitivity. A recent analysis of the diagnostic sensitivity achieved for craniosynostosis from the 100 kGP showed that only 47% of variants had been identified through the panel-based approach in use at that time. Although some of the missing diagnoses were attributable to a failure to call variants included in the contemporaneous Green panel (33% of missing diagnoses), an additional 22% of diagnoses were missed because the gene was considered an Amber or Red gene at the time of analysis, not taking into account more recent discoveries that indicated the gene should have been prioritized more highly [11].
Genomic diagnostics in England has now evolved from the 100 kGP initiative into the NHS England Genomic Medicine Service (www.england.nhs.uk/genomics/nhs-genomic-med-service/; accessed 23 January 2023). This service continues to rely on PanelApp to provide lists of genes to prioritize, however there appears to be no systematic mechanism to ensure that panels remain up to date. Here, we aimed to review the current genes listed as Amber or Red on PanelApp for craniosynostosis, to ascertain whether additional evidence was sufficient to promote a gene to Green status, thus flagging variants within that gene for clinical review by diagnostic laboratories. Additionally, we screened the literature for variants in genes not documented in PanelApp to provide an updated list of genes that should be monitored for further cases or that should already be considered a Green gene. We augmented this list with new data obtained from resequencing a 42-gene panel in 617 affected individuals.

2. Materials and Methods

2.1. Literature Search

Articles were searched on PubMed using “craniosynostosis” as a keyword across a 5-year period from 2018 to end of 2022 (Table 1 and Table S2), as reports prior to this date should have already been incorporated into PanelApp. All exome, genome, or panel-based analyses of patients with craniosynostosis were included and screened for variants in genes listed as Amber or Red on PanelApp (v3, accessed 12 December 2022) [13] (Table S3). Any additional gene not listed on PanelApp with a variant annotated as likely pathogenic/pathogenic was included in the analysis (Table S4). For all genes listed as Amber or Red on PanelApp, a search on PubMed was conducted using the gene name as a keyword across all time periods to identify further case reports to support gene-disease association (Table S3); some of these papers had already been considered in PanelApp. Additionally, we searched for any further published single case reports of craniosynostosis associated with a novel gene to add to the list of genes not described in PanelApp (Table S4).

2.2. Panel-Based Sequencing of a Cohort of Genetically Unsolved Patients with Craniosynostosis

In total, 617 samples (considering a variety of sutures fused) were screened for pathogenic variants in 42 genes (Table S2) using IDT’s hybridization and capture protocol (further details in Supplementary Materials). Probes were designed to ensure that all coding regions of the canonical transcript were captured by at least two probes (probes used to target SOX6 and SMAD3 are detailed in Table S5). Sequencing data were analyzed using amplimap software [27] (including mapping, coverage analysis, and variant calling), and variants were filtered on the basis of rarity (allele frequency in gnomAD [v2.1.1] below 0.000045) [8,28], CADD score ( ≥ 20, or not reported), and likely consequence (missense or more damaging).

2.3. Analysis of Single Cell Transcriptomic Data

For any gene in which there was new, convincing, evidence for variant pathogenicity identified in three or more individuals (from the literature or resequencing analysis), or two or more cases with additional functional evidence, the expression of the gene was analyzed from previously published single cell transcriptomic data of the mouse embryonic day (E) 15.5–17.5 coronal suture [29]. Complete methods and bioinformatic analyses are described in detail by Farmer et al., 2021.

3. Results

Sequencing of 42 genes in 617 unsolved samples identified ten variants considered likely pathogenic. Of these, four were identified in Green genes (three ALX4 variants and one MSX2), and the remaining six variants were identified in Amber genes. The Amber genes included three variants in PRRX1 (which contributed towards the first experimental cohort of patients with craniosynostosis and variants in PRRX1 [30], providing substantial evidence to promote this gene to Green), one splicing variant in SMAD3 (c.206+1G>A; p.(?)), and two truncating variants in SOX6 (Table S3, Figure S1). The two SOX6 variants comprised a 23 bp deletion encompassing the exon 3-intron 3 boundary (c.426_445+13del; p.(?)) and a de novo stop-gain (c.1624G>T; p.(Glu542*)) (Figure S1). For the individual with the SOX6 deletion variant, parental samples were not available for screening. While the identification of additional patients with variants in SMAD3 would be required to promote its current Amber PanelApp status, the two variants in SOX6 provide a significant uplift (40%) to the total number of patients currently described in the literature with craniosynostosis and contribute positively to promoting this gene to Green (Table 2).
Following a framework for evidence-based gene-disease-association classification (Table S1) [57,58], a review of the current literature on variants reported in patients with craniosynostosis alongside the results from our panel-based resequencing analysis (Table 1) suggests that an additional 16 genes should be promoted to Green status (Table 2), bringing the total number of Green genes to 81 (a 25% increase). Four of these are currently classified as Amber (MASP1, NFIA, PRRX1, and SOX6), six genes are annotated as Red (ADAMTSL4, AHDC1, FBN1, FGF9, KAT6B, and NFIX), and six genes are not included in PanelApp (ARID1B, BCL11B, CDK13, FBXO11, IL6ST, and MAN2B1). Further details on these 16 proposed new Green genes are provided in the Supplementary Materials section.
Single cell transcriptomic data from the mouse E15.5–17.5 coronal suture was analyzed to provide additional information for interpreting the pathophysiological mechanisms associated with the 16 genes identified. Nine of these genes displayed generalized expression across all cell populations, but only Nfia, Nfix and Prrx1 were shown to be highly expressed in all clusters (Figure S2). The remaining seven genes showed specific expression patterns (Figure S3), with Bcl11b and Sox6 expressed in osteogenic cells, while Il6st was predominately expressed in non-osteogenic cell clusters. Masp1 was identified in the suture periosteum and Fgf9 showed low but specific expression within cells of the suprasutural layer. Fbn1 and Adamtsl4 showed specific expression within cells of the ectocranial layers, although Fbn1 was more widely expressed in the ectocranial clusters. Details on the role of each cell population in the development of the coronal suture were discussed previously [29].

4. Discussion

Based on the identification of three or more individuals harboring variants associated with congruent phenotypes and likely damaging variants in a common gene, to date, there are 65 genes classified as Green in PanelApp. Of those, 24 (37%) may be considered “core” craniosynostosis-associated genes, in which variants of a particular molecular type are associated with craniosynostosis in over 50% of the individuals and are considered to perturb fundamental components in the biology of cranial suturogenesis. The remaining genes are those in which craniosynostosis is a phenotype less frequently associated with pathogenic variants within that gene, although likely causally associated. This latter grouping includes some examples in which there is a wider disturbance in osteogenesis, owing to aberrant osteoblast or osteoclast activity.
Of the 16 genes presented here as newly associated craniosynostosis genes, PRRX1 and FGF9 may be considered as core genes. PRRX1 encodes the mammalian paired-related homeobox 1 transcription factor, a member of the PRD class of homeobox transcription factors that regulate several aspects of embryonic development [59]. Post-natal calvarial stem cells expressing Prrx1 have been shown to reside exclusively in the calvarial suture niche [60], suggesting a requirement for PRRX1 regarding suture patency during early development. In support, Prrx1 has been shown to be widely expressed within the mouse coronal suture at E15.5 [29] (Figure S2). Postnatal skeletal stem cells expressing Prrx1 were also shown to respond to WNT signaling by differentiating into osteoblasts and can regenerate bone upon heterotopic transplantation [60], supporting a key role for PRRX1 in the maintenance of the sutural mesenchyme and flanking bone fronts.
FGF9 encodes fibroblast growth factor 9, an essential growth factor for intramembranous ossification. Positive differentiation signals emanating from osteoid (a collagenous unmineralized matrix produced by osteoblasts), alongside provision of growth factors (including FGF9) from the dura mater underlying the suture [61,62], stimulate osteogenesis of the surrounding bone fronts. In support, analysis of single cell data shows Fgf9 predominantly expressed within the suprasutural layer, but also within small populations of cells occupying the outer dura mater and osteoprogenitors (Figure S3) [29]. This spatial distribution permits signaling interactions between mesenchymal populations and osteogenic cells, thus controlling differentiation and proliferation of osteoblasts to establish the growing bone fronts flanking the suture [63,64,65]. Notably, a mouse semidominant mutant (Elbow knee synostosis; Eks) is caused by the amino acid substitution p.(Asn143Thr) in Fgf9 and manifests elbow joint fusions, knee joint dysplasia, and craniosynostosis [46,66,67]; importantly, variants in multiple members of the FGF receptor family cause several classical craniosynostosis syndromes, including Apert, Crouzon, Pfeiffer and Muenke syndromes [9].
The remaining 14 craniosynostosis-associated genes can be broadly divided into five categories of pathophysiology: defects in the extracellular matrix (ECM) (ADAMTSL4 and FBN1); regulators of cell cycle-progression and/or genome stability (CDK13 and FBXO11); chromatinopathies (ARID1B and KAT6B); bone osteogenesis, resorption, and homeostasis (IL6ST, MAN2B1, and MASP1); and abnormalities in regulators of cell fate and differentiation (AHDC1, BCL11B, NFIA, NFIX, and SOX6). Each of these categories, which are not mutually exclusive, is discussed briefly in turn (further details on each gene are described in the Supplementary Materials).
The ECM plays an important role in cell signaling by eliciting cues for cell proliferation, migration, and differentiation. For example, fibrillin-1 (FBN1) (an ECM glycoprotein) mediates the activation of transforming growth factor β (TGF-β) [9,40], which is known to be upregulated in osteoblasts [62]. This interaction is stabilized by ECM-binding proteins (including ADAMTSL4) at the cell matrix interface [68,69,70]; expression of Adamtsl4 in the mouse coronal suture was identified within the ectocranial layers, overlapping with sites of expression of Fbn1 (Figure S3).
Previously, hypomorphic variants in genes involved in the regulation of cell division, including CDC45 and RECQL4 (both Green genes) were reported in patients with craniosynostosis [9]. Members of the cyclin-dependent kinases (CDKs) regulate cell-cycle progression and gene expression through controlling cell-cycle checkpoints, and phosphorylation status and activity of splicing regulators [52]. Dysregulation of a number of CDKs promotes cell proliferation and is a hallmark of several cancers [71]. In addition, DNA damage response pathways respond to genotoxic stress induced by the presence of deleterious changes in the DNA sequence, by inducing cell cycle arrest and repair mechanisms. FBXO11 belongs to the F-Box family of proteins which mediate protein-protein interaction for ubiquitin-mediated proteolysis [72]; FBXO11 constitutes one subunit of an E3-ubiqitin ligase complex, and functions to recognize substrates for degradation [73], thus controlling genome stability. Both Cdk13 and Fbxo11 are expressed across all populations of the coronal suture (Figure S2). The importance of maintaining the balance between cell proliferation and differentiation within the suture is discussed later.
In line with recent reports, we identified chromatin modifiers as a category of pleiotropic genes associated with craniosynostosis [22,74], whereby the underlying genetic mechanism is the disruption of a component of epigenetic machinery (writers, erasers, and readers). In keeping with the heterogenous function of chromatin modifiers, the expression of Arid1b and Kat6b is generally widespread across tissues of the mouse coronal suture (Figure S2). Targets of epigenetic modification include the DNA itself through alterations to methylation status, or by modification of the DNA-associated histone proteins [75]. The effect of variation within these genes is expected to be widespread, although a defining feature of patients with chromatinopathies is usually the presence of intellectual disabilities [75].
Genes involved in immunity have previously been highlighted as important molecules in the maintenance of the balance between bone growth, mediated by osteoblasts, and resorption, mediated by osteoclasts [9]. IL6ST encodes GP130, a cytokine receptor and transducer of IL6-mediated cytokine signaling. Perturbations in cytokine signaling affect bone remodeling due to a defect in osteoclast differentiation; for example, biallelic loss-of-function variants in the interleukin 11 (IL-11) co-receptor, IL11RA, cause craniosynostosis, possibly owing to an osteoclast defect and subsequent failure to break down the bone matrix. In support, Il6st was predominantly expressed in the non-osteogenic populations above and below the suture (Figure S3). MASP1, which encodes the mannan-binding lectin serine protease-1, functions in the lectin pathway of complement. Osteoclast-derived complement factors were shown to stimulate osteoblast differentiation, shifting the balance towards increased bone growth potential [76,77]. Consistent with this function, Masp1 exhibits specific expression within a pre-osteoblast population of the coronal suture (Figure S3). MAN2B1 encodes α-D-mannosidase, which functions in the lysosomal maturation of N-linked glycoproteins. Biallelic defects in MAN2B1 lead to multisystem accumulation of undigested oligosaccharides in the lysosomes, affecting the function of many cell types including osteogenic cells.
For the maintenance of the cranial suture, a population of undifferentiated stem cells must persist within the mid-sutural mesenchyme [9]. A disruption in the delicate balance of proliferation and differentiation, associated with increased cell proliferation and/or accelerated osteogenic differentiation, may result in craniosynostosis. The genes AHDC1, BCL11B, NFIA, NFIX and SOX6 all encode transcription factors, the haploinsufficiency of which may perturb cell regulation in specific contexts. SOX6 has previously been shown to function as a tumor suppressor [78,79], limiting cell proliferation; in support, we identified expression of Sox6 within the sutural mesenchyme and progenitor cell populations surrounding the suture (Figure S3). The expression of Bcl11b is specifically enriched within the osteoprogenitor cell populations (Figure S3); this finding is consistent with studies in mice that have highlighted an essential role of Bcl11b in suture biogenesis. Complete loss of Bcl11b in mice was associated with increased proliferation of osteoprogenitors and premature osteoblast differentiation, leading to synostoses of facial and calvarial sutures [80]. Additionally, mutation of a critical residue involved in binding the RBBP4-MTA1 complex, p.(Arg3Ser), was shown to cause coronal craniosynostosis at post-natal day 0 [49]. Cells expressing Ahdc1, Nfia, and Nfix showed more generalized expression across populations of the coronal suture (Figure S2). Accordingly, these genes are known to regulate multiple embryonic lineages and pathogenic variants were shown to cause varying phenotypes, with neurodevelopmental disorder a common feature [33,39,81].

5. Conclusions

A literature review of single case reports, and exome-, genome-, or panel-based analyses of patients with craniosynostosis, alongside the resequencing of 617 individuals with craniosynostosis for variants in 42 genes, identified 16 genes that should be newly promoted to Green on PanelApp according to gene-disease association criteria. Inclusion of these genes will facilitate the identification of additional variants in patients recruited to the 100 kGP. We highlight two core genes (FGF9, PRRX1) in which variants may impact key aspects of cranial suture biology, but for the majority of the genes it is likely that craniosynostosis is a rare consequence of mutation. While efforts have been made to update the craniosynostosis panel over recent years, this report provides (to our knowledge) the first systematic update of genes newly implicated in craniosynostosis since 2019. Additionally, the heterogenous nature of craniosynostosis is underlined, giving significant uplift to the number of genes identified in the long tail of rarer genetic diagnoses. In genes for which only one or two patients have currently been identified with a likely pathogenic variant, we hope this work will provide a resource for the identification and analysis of additional cases in the future.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes14030615/s1, Figure S1: Pedigree figures and dideoxy-sequencing confirmation of SOX6 (NM_033326.3) and SMAD3 (NM_005902.4) variants; Figure S2: Genes displaying widespread expression across cell clusters; Figure S3: Coronal suture single cell transcriptomic map and specific expression patterns of seven genes; Table S1: Criteria for a diagnostic-grade Green gene on PanelApp; Table S2: Whole exome-, genome-, or panel-based analyses of patients with craniosynostosis between 2018–2022; Table S3: PanelApp Amber and Red genes and updated evidence for their association with craniosynostosis.; Table S4: Genes not currently listed in PanelApp but with one or more variants described in a patient with craniosynostosis; Table S5: Coordinates of the probes used in the target capture analysis of SOX6 and SMAD3.

Author Contributions

Conceptualization, R.S.T., S.R.F.T. and A.O.M.W.; methodology, R.S.T. and E.C.; formal analysis, R.S.T. and S.R.F.T.; patient identification and recruitment, A.W. and L.C.W.; investigation, R.S.T.; writing—original draft preparation, R.S.T.; writing—review and editing, R.S.T., S.R.F.T. and A.O.M.W.; supervision, S.R.F.T. and A.O.M.W.; funding acquisition, S.R.F.T. and A.O.M.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by a Doctoral Training Programme studentship funded jointly by the Radcliffe Department of Medicine, Exeter College (Oxford) Usher Cunningham Scholarship and the MRC (R.S.T.), the NIHR Oxford Biomedical Research Centre Programme (S.R.F.T., A.O.M.W.) and the MRC through a Project Grant MR/T031670/1 (A.O.M.W.).

Institutional Review Board Statement

Patient recruitment and genetic analyses were performed under the protocol for ‘Genetic Basis of Craniofacial Malformations’ (London—Riverside REC (09/H0706/20)).

Informed Consent Statement

Participants or their legal guardians gave informed written consent to participate in the study before taking part.

Data Availability Statement

All discussed data are presented in the article or Supplementary Materials.

Acknowledgments

We wish to thank all expert reviewers who facilitate regular updates to the craniosynostosis panel on PanelApp, and D’Juan Farmer and Gage Crump for use of the published single cell data of the mouse E15.5 coronal suture. We also acknowledge support from the NIHR UK Rare Genetic Disease Research Consortium.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Tønne, E.; Due-Tønnessen, B.J.; Wiig, U.; Stadheim, B.F.; Meling, T.R.; Helseth, E.; Heimdal, K.R. Epidemiology of craniosynostosis in Norway. J. Neurosurg. Pediatr. 2020, 26, 68–75. [Google Scholar] [CrossRef] [PubMed]
  2. Cornelissen, M.; Ottelander, B.; Rizopoulos, D.; van der Hulst, R.; Mink van der Molen, A.; van der Horst, C.; Delye, H.; van Veelen, M.L.; Bonsel, G.; Mathijssen, I. Increase of prevalence of craniosynostosis. J. Craniomaxillofac. Surg. 2016, 44, 1273–1279. [Google Scholar] [CrossRef] [PubMed]
  3. Justice, C.M.; Yagnik, G.; Kim, Y.; Peter, I.; Jabs, E.W.; Erazo, M.; Ye, X.; Ainehsazan, E.; Shi, L.; Cunningham, M.L.; et al. A genome-wide association study identifies susceptibility loci for nonsyndromic sagittal craniosynostosis near BMP2 and within BBS9. Nat. Genet. 2012, 44, 1360–1364. [Google Scholar] [CrossRef] [PubMed]
  4. Justice, C.M.; Cuellar, A.; Bala, K.; Sabourin, J.A.; Cunningham, M.L.; Crawford, K.; Phipps, J.M.; Zhou, Y.; Cilliers, D.; Byren, J.C.; et al. A genome-wide association study implicates the BMP7 locus as a risk factor for nonsyndromic metopic craniosynostosis. Hum. Genet. 2020, 139, 1077–1090. [Google Scholar] [CrossRef] [PubMed]
  5. Sanchez-Lara, P.A.; Carmichael, S.L.; Graham, J.M.; Jr Lammer, E.J.; Shaw, G.M.; Ma, C.; Rasmussen, S.A. National Birth Defects Prevention Study: Fetal constraint as a potential risk factor for craniosynostosis. Am. J. Med. Genet. A 2010, 152A, 394–400. [Google Scholar] [CrossRef] [PubMed]
  6. Wilkie, A.O.M.; Johnson, D.; Wall, S.A. Clinical genetics of craniosynostosis. Curr. Opin. Pediatr. 2017, 29, 622–628. [Google Scholar] [CrossRef]
  7. Timberlake, A.T.; Furey, C.G.; Choi, J.; Nelson-Williams, C.; Yale Center for Genome Analysis; Loring, E.; Galm, A.; Kahle, K.T.; Steinbacher, D.M.; Larysz, D.; et al. De novo mutations in inhibitors of Wnt, BMP, and Ras/ERK signaling pathways in non-syndromic midline craniosynostosis. Proc. Natl. Acad. Sci. USA 2017, 114, E7341–E7347. [Google Scholar] [CrossRef]
  8. Calpena, E.; Cuellar, A.; Bala, K.; Swagemakers, S.M.A.; Koelling, N.; McGowan, S.J.; Phipps, J.M.; Balasubramanian, M.; Cunningham, M.L.; Douzgou, S.; et al. SMAD6 variants in craniosynostosis: Genotype and phenotype evaluation. Genet. Med. 2020, 22, 1498–1506. [Google Scholar] [CrossRef]
  9. Twigg, S.R.F.; Wilkie, A.O.M. A Genetic-Pathophysiological Framework for Craniosynostosis. Am. J. Hum. Genet. 2015, 97, 359–377. [Google Scholar] [CrossRef]
  10. Goos, J.A.C.; Mathijssen, I.M.J. Genetic Causes of Craniosynostosis: An Update. Mol. Syndromol. 2019, 10, 6–23. [Google Scholar] [CrossRef]
  11. Hyder, Z.; Calpena, E.; Pei, Y.; Tooze, R.S.; Brittain, H.; Twigg, S.R.F.; Cilliers, D.; Morton, J.E.V.; McCann, E.; Weber, A.; et al. Evaluating the performance of a clinical genome sequencing program for diagnosis of rare genetic disease, seen through the lens of craniosynostosis. Genet. Med. 2021, 23, 2360–2368. [Google Scholar] [CrossRef]
  12. Smedley, D.; Smith, K.R.; Martin, A.; Thomas, E.A.; McDonagh, E.M.; Cipriani, V.; Ellingford, J.M.; Arno, G.; Tucci, A.; Vandrovcova, J.; et al. 100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care-Preliminary Report. N. Eng. J. Med. 2021, 385, 1868–1880. [Google Scholar]
  13. Martin, A.R.; Williams, E.; Foulger, R.E.; Leigh, S.; Daugherty, L.C.; Niblock, O.; Leong, I.U.S.; Smith, K.R.; Gerasimenko, O.; Haraldsdottir, E.; et al. PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels. Nat. Genet. 2019, 51, 1560–1565. [Google Scholar] [CrossRef]
  14. Lee, E.; Le, T.; Zhu, Y.; Elakis, G.; Turner, A.; Lo, W.; Venselaar, H.; Verrenkamp, C.A.; Snow, N.; Mowat, D.; et al. A craniosynostosis massively parallel sequencing panel study in 309 Australian and New Zealand patients: Findings and recommendations. Genet. Med. 2018, 20, 1061–1068. [Google Scholar] [CrossRef]
  15. Clarke, C.M.; Fok, V.T.; Gustafson, J.A.; Smyth, M.D.; Timms, A.E.; Frazar, C.D.; Smith, J.D.; Birgfeld, C.B.; Lee, A.; Ellenbogen, R.G.; et al. Single suture craniosynostosis: Identification of rare variants in genes associated with syndromic forms. Am. J. Med. Genet. A 2018, 176, 290–300. [Google Scholar] [CrossRef]
  16. Topa, A.; Rohlin, A.; Andersson, M.K.; Fehr, A.; Lovmar, L.; Stenman, G.; Kolby, L. NGS targeted screening of 100 Scandinavian patients with coronal synostosis. Am. J. Med. Genet. A 2020, 182, 348–356. [Google Scholar] [CrossRef]
  17. Timberlake, A.T.; Jin, S.C.; Nelson-Williams, C.; Wu, R.; Furey, C.G.; Islam, B.; Haider, S.; Loring, E.; Galm, A.; Yale Center for Genome Analysis; et al. Mutations in TFAP2B and previously unimplicated genes of the BMP, Wnt, and Hedgehog pathways in syndromic craniosynostosis. Proc. Natl. Acad. Sci. USA 2019, 116, 15116–15121. [Google Scholar] [CrossRef]
  18. Suzuki, T.; Suzuki, T.; Raveau, M.; Miyake, N.; Sudo, G.; Tsurusaki, Y.; Watanabe, T.; Sugaya, Y.; Tatsukawa, T.; Mazaki, E.; et al. A recurrent PJA1 variant in trigonocephaly and neurodevelopmental disorders. Ann. Clin. Transl. Neurol. 2020, 7, 1117–1131. [Google Scholar] [CrossRef]
  19. Yoon, J.G.; Hahn, H.M.; Choi, S.; Kim, S.J.; Aum, S.; Yu, J.W.; Park, E.K.; Shim, K.W.; Lee, M.G.; Kim, Y.O. Molecular Diagnosis of Craniosynostosis Using Targeted Next-Generation Sequencing. Neurosurgery 2020, 87, 294–302. [Google Scholar] [CrossRef]
  20. Wu, Y.; Peng, M.; Chen, J.; Suo, J.; Zou, S.; Xu, Y.; Wilkie, A.O.M.; Zou, W.; Mu, X.; Wang, S. A custom-designed panel sequencing study in 201 Chinese patients with craniosynostosis revealed novel variants and distinct mutation spectra. J. Genet. Genom. 2021, 48, 167–171. [Google Scholar] [CrossRef]
  21. Alghamdi, M.; Alhumsi, T.R.; Altweijri, I.; Alkhamis, W.H.; Barasain, O.; Cardona-Londono, K.J.; Ramakrishnan, R.; Guzman-Vega, F.J.; Arold, S.T.; Ali, G.; et al. Clinical and Genetic Characterization of Craniosynostosis in Saudi Arabia. Front. Pediatr. 2021, 9, 582816. [Google Scholar] [CrossRef] [PubMed]
  22. Tønne, E.; Due-Tønnessen, B.J.; Mero, I.L.; Wiig, U.S.; Kulseth, M.A.; Vigeland, M.D.; Sheng, Y.; von der Lippe, C.; Tveten, K.; Meling, T.R.; et al. Benefits of clinical criteria and high-throughput sequencing for diagnosing children with syndromic craniosynostosis. Eur. J. Hum. Genet. 2021, 29, 920–929. [Google Scholar] [CrossRef] [PubMed]
  23. Chen, J.; Zhang, P.; Peng, M.; Liu, B.; Wang, X.; Du, S.; Lu, Y.; Mu, X.; Lu, Y.; Wang, S.; et al. An additional whole-exome sequencing study in 102 panel-undiagnosed patients: A retrospective study in a Chinese craniosynostosis cohort. Front. Genet. 2022, 13, 967688. [Google Scholar] [CrossRef] [PubMed]
  24. Tønne, E.; Due-Tønnessen, B.J.; Vigeland, M.D.; Amundsen, S.S.; Ribarska, T.; Asten, P.M.; Sheng, Y.; Helseth, E.; Gilfillan, G.D.; Mero, I.L.; et al. Whole-exome sequencing in syndromic craniosynostosis increases diagnostic yield and identifies candidate genes in osteogenic signaling pathways. Am. J. Med. Genet. A 2022, 188, 1464–1475. [Google Scholar] [CrossRef] [PubMed]
  25. Timberlake, A.T.; Kiziltug, E.; Jin, S.C.; Nelson-Williams, C.; Loring, E.; Yale Center for Genome Analysis; Allocco, A.; Marlier, A.; Banka, S.; Stuart, H.; et al. De novo mutations in the BMP signaling pathway in lambdoid craniosynostosis. Hum. Genet. 2023, 142, 21–32. [Google Scholar] [CrossRef]
  26. Tooze, R.S.; Calpena, E.; Twigg, S.R.F.; D’Arco, F. Genomics England Research C, Wakeling EL, Wilkie AOM: Craniosynostosis, inner ear, and renal anomalies in a child with complete loss of SPRY1 (sprouty homolog 1) function. J. Med. Genet. 2022. Epub ahead of print. [Google Scholar] [CrossRef]
  27. Koelling, N.; Bernkopf, M.; Calpena, E.; Maher, G.J.; Miller, K.A.; Ralph, H.K.; Goriely, A.; Wilkie, A.O.M. Amplimap: A versatile tool to process and analyze targeted NGS data. Bioinformatics 2019, 35, 5349–5350. [Google Scholar] [CrossRef]
  28. Whiffin, N.; Minikel, E.; Walsh, R.; O’Donnell-Luria, A.H.; Karczewski, K.; Ing, A.Y.; Barton, P.J.R.; Funke, B.; Cook, S.A.; MacArthur, D.; et al. Using high-resolution variant frequencies to empower clinical genome interpretation. Genet. Med. 2017, 19, 1151–1158. [Google Scholar] [CrossRef]
  29. Farmer, D.T.; Mlcochova, H.; Zhou, Y.; Koelling, N.; Wang, G.; Ashley, N.; Bugacov, H.; Chen, H.J.; Parvez, R.; Tseng, K.C.; et al. The developing mouse coronal suture at single-cell resolution. Nat. Commun. 2021, 12, 4797. [Google Scholar] [CrossRef]
  30. Tooze, R.S.; Miller, K.; Swagemakers, S.; Mcgowan, S.; Boute, O.; Collet, C.; Johnson, D.; Laffargue, F.; Leeuw, N.D.; Morton, J.; et al. Pathogenic variants in the paired-related homeobox 1 (PRRX1) gene are associated with craniosynostosis [Conference Abstract]. In Proceedings of the European Society of Human Genetics Conference, Vienna, Austria, 11–14 June 2022. [Google Scholar]
  31. Durmaz, C.D.; Altiner, S. MASP1-related 3MC syndrome in a patient from Turkey. Am. J. Med. Genet. A 2021, 185, 2267–2270. [Google Scholar] [CrossRef]
  32. Atik, T.; Koparir, A.; Bademci, G.; Foster, J., 2nd; Altunoglu, U.; Mutlu, G.Y.; Bowdin, S.; Elcioglu, N.; Tayfun, G.A.; Atik, S.S.; et al. Novel MASP1 mutations are associated with an expanded phenotype in 3MC1 syndrome. Orphanet J. Rare Dis. 2015, 10, 128. [Google Scholar] [CrossRef]
  33. Tolchin, D.; Yeager, J.P.; Prasad, P.; Dorrani, N.; Russi, A.S.; Martinez-Agosto, J.A.; Haseeb, A.; Angelozzi, M.; Santen, G.W.E.; Ruivenkamp, C.; et al. De Novo SOX6 Variants Cause a Neurodevelopmental Syndrome Associated with ADHD, Craniosynostosis, and Osteochondromas. Am. J. Hum. Genet. 2020, 106, 830–845. [Google Scholar] [CrossRef]
  34. Tagariello, A.; Heller, R.; Greven, A.; Kalscheuer, V.M.; Molter, T.; Rauch, A.; Kress, W.; Winterpacht, A. Balanced translocation in a patient with craniosynostosis disrupts the SOX6 gene and an evolutionarily conserved non-transcribed region. J. Med. Genet. 2006, 43, 534–540. [Google Scholar] [CrossRef]
  35. Gustafson, J.; Bjork, M.; van Ravenswaaij-Arts, C.M.A.; Cunningham, M.L. Mechanism of Disease: Recessive ADAMTSL4 Mutations and Craniosynostosis with Ectopia Lentis. Case Rep. Genet. 2022, 2022, 3239260. [Google Scholar] [CrossRef]
  36. Gumus, E. Extending the phenotype of Xia-Gibbs syndrome in a two-year-old patient with craniosynostosis with a novel de novo AHDC1 missense mutation. Eur. J. Med. Genet. 2020, 63, 103637. [Google Scholar] [CrossRef]
  37. Miller, K.A.; Twigg, S.R.; McGowan, S.J.; Phipps, J.M.; Fenwick, A.L.; Johnson, D.; Wall, S.A.; Noons, P.; Rees, K.E.; Tidey, E.A.; et al. Diagnostic value of exome and whole genome sequencing in craniosynostosis. J. Med. Genet. 2017, 54, 260–268. [Google Scholar] [CrossRef]
  38. Ritter, A.L.; McDougall, C.; Skraban, C.; Medne, L.; Bedoukian, E.C.; Asher, S.B.; Balciuniene, J.; Campbell, C.D.; Baker, S.W.; Denenberg, E.H.; et al. Variable Clinical Manifestations of Xia-Gibbs syndrome: Findings of Consecutively Identified Cases at a Single Children’s Hospital. Am. J. Med. Genet. A 2018, 176, 1890–1896. [Google Scholar] [CrossRef]
  39. Danda, S.; Datar, C.; Kher, A.; Deshpande, T.; Thomas, M.M.; Oommen, S.P. First reported cases with Xia-Gibbs syndrome from India harboring novel variants in AHDC1. Am. J. Med. Genet. A 2022, 188, 2501–2504. [Google Scholar] [CrossRef]
  40. Adès, L.C.; Sullivan, K.; Biggin, A.; Haan, E.A.; Brett, M.; Holman, K.J.; Dixon, J.; Robertson, S.; Holmes, A.D.; Rogers, J.; et al. FBN1, TGFBR1, and the Marfan-craniosynostosis/mental retardation disorders revisited. Am. J. Med. Genet. A 2006, 140, 1047–1058. [Google Scholar] [CrossRef]
  41. Takenouchi, T.; Hida, M.; Sakamoto, Y.; Torii, C.; Kosaki, R.; Takahashi, T.; Kosaki, K. Severe congenital lipodystrophy and a progeroid appearance: Mutation in the penultimate exon of FBN1 causing a recognizable phenotype. Am. J. Med. Genet. A 2013, 161A, 3057–3062. [Google Scholar] [CrossRef]
  42. Hiraki, Y.; Moriuchi, M.; Okamoto, N.; Ishikawa, N.; Sugimoto, Y.; Eguchi, K.; Sakai, H.; Saitsu, H.; Mizuguchi, T.; Harada, N.; et al. Craniosynostosis in a patient with a de novo 15q15-q22 deletion. Am. J. Med. Genet. A 2008, 146A, 1462–1465. [Google Scholar] [CrossRef] [PubMed]
  43. Sentchordi-Montané, L.; Diaz-Gonzalez, F.; Cátedra-Vallés, E.V.; Heath, K.E. Identification of the third FGF9 variant in a girl with multiple synostosis-comparison of the genotype:phenotype of FGF9 variants in humans and mice. Clin. Genet. 2021, 99, 309–312. [Google Scholar] [CrossRef] [PubMed]
  44. Wu, X.L.; Gu, M.M.; Huang, L.; Liu, X.S.; Zhang, H.X.; Ding, X.Y.; Xu, J.Q.; Cui, B.; Wang, L.; Lu, S.Y.; et al. Multiple synostoses syndrome is due to a missense mutation in exon 2 of FGF9 gene. Am. J. Hum. Genet. 2009, 85, 53–63. [Google Scholar] [CrossRef] [PubMed]
  45. Rodriguez-Zabala, M.; Aza-Carmona, M.; Rivera-Pedroza, C.I.; Belinchon, A.; Guerrero-Zapata, I.; Barraza-Garcia, J.; Vallespin, E.; Lu, M.; Del Pozo, A.; Glucksman, M.J.; et al. FGF9 mutation causes craniosynostosis along with multiple synostoses. Hum. Mutat. 2017, 38, 1471–1476. [Google Scholar] [CrossRef]
  46. Murakami, H.; Okawa, A.; Yoshida, H.; Nishikawa, S.; Moriya, H.; Koseki, H. Elbow knee synostosis (Eks): A new mutation on mouse Chromosome 14. Mamm. Genome 2002, 13, 341–344. [Google Scholar] [CrossRef]
  47. Bashir, R.A.; Dixit, A.; Goedhart, C.; Parboosingh, J.S.; Innes, A.M.; Ferreira, P.; Hasan, S.U.; Au, P.B. Lin-Gettig syndrome: Craniosynostosis expands the spectrum of the KAT6B related disorders. Am. J. Med. Genet. A 2017, 173, 2596–2604. [Google Scholar] [CrossRef]
  48. Mignot, C.; Moutard, M.L.; Rastetter, A.; Boutaud, L.; Heide, S.; Billette, T.; Doummar, D.; Garel, C.; Afenjar, A.; Jacquette, A.; et al. ARID1B mutations are the major genetic cause of corpus callosum anomalies in patients with intellectual disability. Brain 2016, 139, e64. [Google Scholar] [CrossRef]
  49. Goos, J.A.C.; Vogel, W.K.; Mlcochova, H.; Millard, C.J.; Esfandiari, E.; Selman, W.H.; Calpena, E.; Koelling, N.; Carpenter, E.L.; Swagemakers, S.M.A.; et al. A de novo substitution in BCL11B leads to loss of interaction with transcriptional complexes and craniosynostosis. Hum. Mol. Genet. 2019, 28, 2501–2513. [Google Scholar] [CrossRef]
  50. Zhao, X.; Wu, B.; Chen, H.; Zhang, P.; Qian, Y.; Peng, X.; Dong, X.; Wang, Y.; Li, G.; Dong, C.; et al. Case report: A novel truncating variant of BCL11B associated with rare feature of craniosynostosis and global developmental delay. Front. Pediatr. 2022, 10, 982361. [Google Scholar] [CrossRef]
  51. Eto, K.; Machida, O.; Yanagishita, T.; Shimojima Yamamoto, K.; Chiba, K.; Aihara, Y.; Hasegawa, Y.; Nagata, M.; Ishihara, Y.; Miyashita, Y.; et al. Novel BCL11B truncation variant in a patient with developmental delay, distinctive features, and early craniosynostosis. Hum. Genome Var. 2022, 9, 43. [Google Scholar] [CrossRef]
  52. Bostwick, B.L.; McLean, S.; Posey, J.E.; Streff, H.E.; Gripp, K.W.; Blesson, A.; Powell-Hamilton, N.; Tusi, J.; Stevenson, D.A.; Farrelly, E.; et al. Phenotypic and molecular characterisation of CDK13-related congenital heart defects, dysmorphic facial features and intellectual developmental disorders. Genome Med. 2017, 9, 73. [Google Scholar] [CrossRef]
  53. Gregor, A.; Sadleir, L.G.; Asadollahi, R.; Azzarello-Burri, S.; Battaglia, A.; Ousager, L.B.; Boonsawat, P.; Bruel, A.L.; Buchert, R.; Calpena, E.; et al. De Novo Variants in the F-Box Protein FBXO11 in 20 Individuals with a Variable Neurodevelopmental Disorder. Am. J. Hum. Genet. 2018, 103, 305–316. [Google Scholar] [CrossRef]
  54. Schwerd, T.; Krause, F.; Twigg, S.R.F.; Aschenbrenner, D.; Chen, Y.-H.; Borgmeyer, U.; Müller, M.; Manrique, S.; Schumacher, N.; Wall, S.A.; et al. A variant in IL6ST with a selective IL-11 signaling defect in human and mouse. Bone Res. 2020, 8, 24. [Google Scholar] [CrossRef]
  55. Schwerd, T.; Twigg, S.R.F.; Aschenbrenner, D.; Manrique, S.; Miller, K.A.; Taylor, I.B.; Capitani, M.; McGowan, S.J.; Sweeney, E.; Weber, A.; et al. A biallelic mutation in IL6ST encoding the GP130 co-receptor causes immunodeficiency and craniosynostosis. J. Exp. Med. 2017, 214, 2547–2562. [Google Scholar] [CrossRef]
  56. Lipiński, P.; Różdżyńska-Świątkowska, A.; Iwanicka-Pronicka, K.; Perkowska, B.; Pokora, P.; Tylki-Szymańska, A. Long-term outcome of patients with α-mannosidosis—A single center study. Mol. Genet. Metab. Rep. 2022, 30, 100826. [Google Scholar] [CrossRef]
  57. Strande, N.T.; Riggs, E.R.; Buchanan, A.H.; Ceyhan-Birsoy, O.; DiStefano, M.; Dwight, S.S.; Goldstein, J.; Ghosh, R.; Seifert, B.A.; Sneddon, T.P.; et al. Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource. Am. J. Hum. Genet. 2017, 100, 895–906. [Google Scholar] [CrossRef]
  58. Wright, C.F.; Fitzgerald, T.W.; Jones, W.D.; Clayton, S.; McRae, J.F.; van Kogelenberg, M.; King, D.A.; Ambridge, K.; Barrett, D.M.; Bayzetinova, T.; et al. Genetic diagnosis of developmental disorders in the DDD study: A scalable analysis of genome-wide research data. Lancet 2015, 385, 1305–1314. [Google Scholar] [CrossRef]
  59. Holland, P.W.; Booth, H.A.; Bruford, E.A. Classification and nomenclature of all human homeobox genes. BMC Biol. 2007, 5, 47. [Google Scholar] [CrossRef]
  60. Wilk, K.; Yeh, S.A.; Mortensen, L.J.; Ghaffarigarakani, S.; Lombardo, C.M.; Bassir, S.H.; Aldawood, Z.A.; Lin, C.P.; Intini, G. Postnatal Calvarial Skeletal Stem Cells Expressing PRX1 Reside Exclusively in the Calvarial Sutures and Are Required for Bone Regeneration. Stem Cell Rep. 2017, 8, 933–946. [Google Scholar] [CrossRef]
  61. Opperman, L.A. Cranial Sutures as Intramembranous Bone Growth Sites. Dev. Dyn. 2000, 219, 472–485. [Google Scholar] [CrossRef]
  62. Levi, B.; Wan, D.C.; Wong, V.W.; Nelson, E.; Hyun, J.; Longaker, M.T. Cranial suture biology: From pathways to patient care. J. Craniofac. Surg. 2012, 23, 13–19. [Google Scholar] [CrossRef] [PubMed]
  63. Ornitz, D.M.; Marie, P.J. Fibroblast growth factor signaling in skeletal development and disease. Genes Dev. 2015, 29, 1463–1486. [Google Scholar] [CrossRef] [PubMed]
  64. Rice, D.P.; Aberg, T.; Chan, Y.; Tang, Z.; Kettunen, P.J.; Pakarinen, L.; Maxson, R.E.; Thesleff, I. Integration of FGF and TWIST in calvarial bone and suture development. Development 2000, 127, 1845–1855. [Google Scholar] [CrossRef] [PubMed]
  65. Kim, H.J.; Rice, D.P.; Kettunen, P.J.; Thesleff, I. FGF-, BMP- and Shh-mediated signalling pathways in the regulation of cranial suture morphogenesis and calvarial bone development. Development 1998, 125, 1241–1251. [Google Scholar] [CrossRef]
  66. Harada, M.; Murakami, H.; Okawa, A.; Okimoto, N.; Hiraoka, S.; Nakahara, T.; Akasaka, R.; Shiraishi, Y.; Futatsugi, N.; Mizutani-Koseki, Y.; et al. FGF9 monomer-dimer equilibrium regulates extracellular matrix affinity and tissue diffusion. Nat. Genet. 2009, 41, 289–298. [Google Scholar] [CrossRef]
  67. Harada, M.; Akita, K. Mouse fibroblast growth factor 9 N143T mutation leads to wide chondrogenic condensation of long bones. Histochem. Cell Biol. 2020, 153, 215–223. [Google Scholar] [CrossRef]
  68. Gabriel, L.A.; Wang, L.W.; Bader, H.; Ho, J.C.; Majors, A.K.; Hollyfield, J.G.; Traboulsi, E.I.; Apte, S.S. ADAMTSL4, a secreted glycoprotein widely distributed in the eye, binds fibrillin-1 microfibrils and accelerates microfibril biogenesis. Investig. Ophthalmol. Vis. Sci. 2012, 53, 461–469. [Google Scholar] [CrossRef]
  69. Bader, H.L.; Wang, L.W.; Ho, J.C.; Tran, T.; Holden, P.; Fitzgerald, J.; Atit, R.P.; Reinhardt, D.P.; Apte, S.S. A disintegrin-like and metalloprotease domain containing thrombospondin type 1 motif-like 5 (ADAMTSL5) is a novel fibrillin-1-, fibrillin-2-, and heparin-binding member of the ADAMTS superfamily containing a netrin-like module. Matrix Biol. 2012, 31, 398–411. [Google Scholar] [CrossRef]
  70. Tsutsui, K.; Manabe, R.; Yamada, T.; Nakano, I.; Oguri, Y.; Keene, D.R.; Sengle, G.; Sakai, L.Y.; Sekiguchi, K. ADAMTSL-6 is a novel extracellular matrix protein that binds to fibrillin-1 and promotes fibrillin-1 fibril formation. J. Biol. Chem. 2010, 285, 4870–4882. [Google Scholar] [CrossRef]
  71. Ding, L.; Cao, J.; Lin, W.; Chen, H.; Xiong, X.; Ao, H.; Yu, M.; Lin, J.; Cui, Q. The Roles of Cyclin-Dependent Kinases in Cell-Cycle Progression and Therapeutic Strategies in Human Breast Cancer. Int. J. Mol. Sci. 2020, 21, 1960. [Google Scholar] [CrossRef]
  72. Kipreos, E.T.; Pagano, M. The F-box protein family. Genome Biol. 2000, 1, reviews3002.1. [Google Scholar] [CrossRef]
  73. Silverman, J.S.; Skaar, J.R.; Pagano, M. SCF ubiquitin ligases in the maintenance of genome stability. Trends Biochem. Sci. 2012, 37, 66–73. [Google Scholar] [CrossRef]
  74. Zollino, M.; Lattante, S.; Orteschi, D.; Frangella, S.; Doronzio, P.N.; Contaldo, I.; Mercuri, E.; Marangi, G. Syndromic Craniosynostosis Can Define New Candidate Genes for Suture Development or Result from the Non-specifc Effects of Pleiotropic Genes: Rasopathies and Chromatinopathies as Examples. Front. Neurosci. 2017, 11, 587. [Google Scholar] [CrossRef]
  75. Bjornsson, H.T. The Mendelian disorders of the epigenetic machinery. Genome Res. 2015, 25, 1473–1481. [Google Scholar] [CrossRef]
  76. Matsuoka, K.; Park K-a Ito, M.; Ikeda, K.; Takeshita, S. Osteoclast-Derived Complement Component 3a Stimulates Osteoblast Differentiation. J. Bone Miner. Res. 2014, 29, 1522–1530. [Google Scholar] [CrossRef]
  77. Mödinger, Y.; Löffler, B.; Huber-Lang, M.; Ignatius, A. Complement involvement in bone homeostasis and bone disorders. Semin. Immunol. 2018, 37, 53–65. [Google Scholar] [CrossRef]
  78. Wang, Z.; Li, J.; Li, K.; Xu, J. SOX6 is downregulated in osteosarcoma and suppresses the migration, invasion and epithelial-mesenchymal transition via TWIST1 regulation. Mol. Med. Rep. 2018, 17, 6803–6811. [Google Scholar] [CrossRef]
  79. An, C.I.; Ichihashi, Y.; Peng, J.; Sinha, N.R.; Hagiwara, N. Transcriptome Dynamics and Potential Roles of Sox6 in the Postnatal Heart. PLoS ONE 2016, 11, e0166574. [Google Scholar] [CrossRef]
  80. Kyrylkova, K.; Iwaniec, U.T.; Philbrick, K.A.; Leid, M. BCL11B regulates sutural patency in the mouse craniofacial skeleton. Dev. Biol. 2016, 415, 251–260. [Google Scholar] [CrossRef]
  81. Senaratne, T.N.; Quintero-Rivera, F. NFIA-Related Disorder. In GeneReviews(®); Adam, M.P., Everman, D.B., Mirzaa, G.M., Pagon, R.A., Wallace, S.E., Bean, L.J.H., Gripp, K.W., Amemiya, A., Eds.; University of Washington: Seattle, WA, USA, 1993. [Google Scholar]
Table
Table 1. Sequencing of cohorts of patients with craniosynostosis from 2018–2022.
Table 1. Sequencing of cohorts of patients with craniosynostosis from 2018–2022.
CohortNumber of Probands ScreenedSequencing TechnologyPhenotypes Included in the Screen aNumber of Pathogenic/Likely Pathogenic Variants Identified in Each Screen Corresponding to Current PanelApp (v3) Status
GreenAmberRedNull
Australia/New Zealand (Lee et al., 2018) [14]30920-gene panelPatients recruited with a range of sutures fused, with or without syndromic features4021
Seattle (Clarke et al., 2018) [15]397RNA-sequencing,
61 genes screened		Single suture craniosynostosis43119
Scandinavia (Topa et al., 2019) [16]10063-gene panelSyndromic craniosynostosis (78% of the cohort), predominately coronal synostosis66
Yale (Timberlake et al., 2019) [17]12Whole exomeAll syndromic, with single and multi-suture synostosis5 4
Japan (Suzuki et al., 2020) [18] b51Whole exomeAll with trigonocephaly 417
Korea (Yoon et al., 2020) [19]11034-gene panelPatients recruited with syndromic or non-syndromic craniosynostosis and all sutures considered24 1
China (Wu et al., 2021) [20]20117-gene panelCohort consists of patients with syndromic and non-syndromic craniosynostosis51
Saudi Arabia (Alghamdi et al., 2021) [21]28Whole exomeSyndromic craniosynostosis with all sutures considered13 2
100 kGP (Hyder et al., 2021) [11]114Whole genomePatients recruited with syndromic or non-syndromic craniosynostosis and all sutures considered123316
Norway (Tønne et al., 2021) [22]38172-gene panelPatients recruited with syndromic or non-syndromic craniosynostosis and all sutures considered59 45
China (Chen et al., 2022) [23]26417-gene panel (264 individuals), whole-exome sequencing (n = 102, 39%)Patients recruited with syndromic or non-syndromic craniosynostosis and all sutures considered1432 4
Norway (Tønne et al., 2022) [24]10Whole exomeAll patients with syndromic craniosynostosis that were negative in the previous Tønne screen [22] 1 4
Yale (Timberlake et al., 2023) [25]25Whole exomeAll patients displayed lambdoid synostosis 114
Oxford (Tooze et al., 2022) [26]61742-gene panel (Table S2)Patients recruited with syndromic or non-syndromic craniosynostosis and all sutures considered46
a See Table S2 for further information. b Only variants confirmed by dideoxy-sequencing within this study were included in variant counts.
Table
Table 2. Genes with sufficient evidence to be updated to Green PanelApp status.
Table 2. Genes with sufficient evidence to be updated to Green PanelApp status.
Gene.Current PanelMode of InheritanceBroad Categories of PathophysiologyLiterature
MASP1AmberBiallelicBone osteogenesis, resorption, and homeostasisTwo reviews identify a prevalence of 27–31% of patients with craniosynostosis and 3MC syndrome and a variant in MASP1 [31,32].
NFIAAmberMonoallelicRegulator of cell fate and differentiationFour patients identified in independent screens [19,22,23,24].
PRRX1AmberMonoallelicRegulator of cell fate and differentiationThere are 17 patients from 14 independent families with rare heterozygous variants in PRRX1, predicting loss of function variants or missense variants affecting the homeodomain [30].
SOX6AmberMonoallelicRegulator of cell fate and differentiationSeven independent families with loss of function variants in SOX6 and craniosynostosis; five of these are published [23,33,34] and two were identified in a screen of 617 patients without a genetic diagnosis to their craniosynostosis [this study; Table S3].
ADAMTSL4RedBiallelicRegulator of the extracellular matrixMore than 12 cases of ectopia lentis and craniosynostosis are associated with recessive variants in ADAMTSL4 [35].
AHDC1RedMonoallelicRegulator of cell fate and differentiationThere are three individuals reported with bona fide craniosynostosis and variants in AHDC1 [36,37,38], a further four individuals are described with variants in AHDC1 and suspected craniosynostosis [22,39].
FBN1RedMonoallelicRegulator of the extracellular matrixThere are five likely pathogenic de novo variants reported in independent families and one deletion which includes FBN1 [19,37,40,41,42].
FGF9RedMonoallelicRegulator of cell fate and differentiationThree likely pathogenic variants have been reported in independent families; one variant segregates in 12 individuals in the same family and another variant was inherited from an affected father [43,44,45]. A missense substitution, p.(Asn143Thr), in murine Fgf9 results in a phenotype similar to multiple synostoses syndrome 3, with craniosynostosis [46].
KAT6BRedMonoallelicChromatinopathyThree loss of function variants have been identified in patients with craniosynostosis and a phenotype similar to Lin-Gettig syndrome [22,47].
NFIXRedMonoallelicRegulator of cell fate and differentiationFour families are reported with variants in NFIX. Only one of these variants does not affect a functional domain (p.(Met48Lys)), but it is reported in ClinVar as likely pathogenic for Malan overgrowth syndrome [22,25].
ARID1BAbsentMonoallelicChromatinopathyFour independent families have been described with loss-of-function variants in ARID1B and craniosynostosis with developmental delay [11,18,23,48].
BCL11BAbsentMonoallelicRegulator of cell fate and differentiationThere are seven families with variants in BCL11B and confirmed craniosynostosis [49,50,51].
CDK13AbsentMonoallelicCell-cycle regulator/genome stabilityFour independent cases identified within the literature in patients with craniosynostosis [11,22,52].
FBXO11AbsentMonoallelicCell-cycle regulator/genome stabilityThree independent cases confirmed in patients [11,53].
IL6STAbsentBiallelicBone osteogenesis, resorption, and homeostasisTwo cases of recessive variants in IL6ST and craniosynostosis with additional animal models which phenocopy the human presentation [54,55].
MAN2B1AbsentBiallelicBone osteogenesis, resorption, and homeostasisThree independent families with recessive variants in MAN2B1 and craniosynostosis, although not all individuals with recessive variants in MAN2B1 develop craniosynostosis [11,22,56].
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Tooze, R.S.; Calpena, E.; Weber, A.; Wilson, L.C.; Twigg, S.R.F.; Wilkie, A.O.M. Review of Recurrently Mutated Genes in Craniosynostosis Supports Expansion of Diagnostic Gene Panels. Genes 2023, 14, 615. https://doi.org/10.3390/genes14030615

AMA Style

Tooze RS, Calpena E, Weber A, Wilson LC, Twigg SRF, Wilkie AOM. Review of Recurrently Mutated Genes in Craniosynostosis Supports Expansion of Diagnostic Gene Panels. Genes. 2023; 14(3):615. https://doi.org/10.3390/genes14030615

Chicago/Turabian Style

Tooze, Rebecca S., Eduardo Calpena, Astrid Weber, Louise C. Wilson, Stephen R. F. Twigg, and Andrew O. M. Wilkie. 2023. "Review of Recurrently Mutated Genes in Craniosynostosis Supports Expansion of Diagnostic Gene Panels" Genes 14, no. 3: 615. https://doi.org/10.3390/genes14030615

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop