The face signature of fibrodysplasia ossificans progressiva

Hammond, Peter; Suttie, Michael; Hennekam, Raoul C. M.; Allanson, Judith; Shore, Eileen M.; Kaplan, Frederick S.

doi:10.1002/ajmg.a.35346

Cited by 41 publications

(50 citation statements)

References 34 publications

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“…In addition, many FOP patients have a small mandible. Variably dysmorphic facial features in the regions of midface and jaw suggested by Hammond et al [2012] are likely related to the canonical ACVR1 mutation and not described in patients with other mutations so far. Ectodermal features have been described in patients with other mutations too.…”

Section: Genotype-phenotype Correlationmentioning

confidence: 99%

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Fibrodysplasia Ossificans Progressiva: Clinical Course, Genetic Mutations and Genotype-Phenotype Correlation

Hüning

Gillessen‐Kaesbach²

2014

Mol Syndromol

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Fibrodysplasia ossificans progressiva (FOP, MIM 135100) is a rare autosomal dominant genetic disorder and the most disabling condition of heterotopic (extraskeletal) ossification in humans. Mutations in the ACVR1 gene (MIM 102576) were identified as a genetic cause of FOP [Shore et al., 2006]. Most patients with FOP have the same recurrent single nucleotide change c.617G>A, p.R206H in the ACVR1 gene. Furthermore, 11 other mutations in the ACVR1 gene have been described as a cause of FOP. Here, we review phenotypic and molecular findings of 130 cases of FOP reported in the literature from 1982 to April 2014 and discuss possible genotype-phenotype correlations in FOP patients.

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Section: Genotype-phenotype Correlationmentioning

confidence: 99%

“…Some patients are reported with slow hair growth, which was also a feature occurring in the second or third decade of life. Hammond et al [2012] suggested that FOP patients often have longer, narrower faces than age-sex matched controls -males more so than females. In addition, many FOP patients have a small mandible.…”

Section: Genotype-phenotype Correlationmentioning

confidence: 99%

Fibrodysplasia Ossificans Progressiva: Clinical Course, Genetic Mutations and Genotype-Phenotype Correlation

Hüning

Gillessen‐Kaesbach²

2014

Mol Syndromol

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“…Signature graphs have been successfully used recently to link extreme facial dysmorphism in patients with epilepsy to novel micro-deletions and duplications 17,18 and rare conditions such as fibrodysplasia ossificans progressiva. 19 Face-brain shape correlation studies in mouse models have also benefitted from signature graph techniques. 20 Further technical details are provided as supplementary information and elsewhere.…”

Section: Methodsmentioning

confidence: 99%

Craniofacial characteristics of fragile X syndrome in mouse and man

Heulens

Suttie²,

Постнов

et al. 2012

Eur J Hum Genet

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For a disorder as common as fragile X syndrome, the most common hereditary form of cognitive impairment, the facial features are relatively ill defined. An elongated face and prominent ears are the most commonly accepted dysmorphic hallmarks. We analysed 3D facial photographs of 51 males and 15 females with full FMR1 mutations and 9 females with a premutation using dense-surface modelling techniques and a new technique that forms a directed graph with normalized face shapes as nodes and edges linking those with closest dysmorphism. In addition to reconfirming known features, we confirmed the occurrence of some at an earlier age than previously recorded. We also identified as yet unrecorded facial characteristics such as reduced facial depth, hypoplasticity of the nasal bone-cartilage interface and narrow mid-facial width exaggerating ear prominence. As no consistent craniofacial abnormalities had been reported in animal models, we analysed micro-CT images of the fragile X mouse model. Results indicated altered dimensions in the mandible and both outer and inner skull, with the latter potentially reflecting differences in neuroanatomy. We extrapolated the mouse results to face shape differences of the human fragile X face.

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“…20,30 The agreement of clinical categorization (Table 1) and classification using DSM representation of face shape was estimated from 20 random 90% to 10% training-unseen test pairs of subject subsets (stratified with respect to affected or unaffected status) by using receiver operating characteristic (ROC) curve analysis. To analyze the faces of those who were HE, we introduced signature graph [28][29][30] cluster analysis. Sequences of 35 contiguously aged control faces generated age-matched means for comparison and normalization.…”

Section: Face Analysismentioning

confidence: 99%

“…27 In this study of South African children, we used face shape to induce classification schemes and tested agreement with clinical FASD categorization. The more heterogeneous phenotype of HE forced us to introduce a clustering technique, 28 signature graph analysis, 29,30 which normalizes face shape and links individuals with similar facial dysmorphism. Signature graph analysis identified half of our HE group as having facial dysmorphism that was more FAS-like than control-like.…”

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confidence: 99%

Facial Dysmorphism Across the Fetal Alcohol Spectrum

2013

PEDIATRICS

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WHAT IS KNOWN ON THIS SUBJECT: Prenatal alcohol exposure causes a continuum of effects. The most severe phenotype, fetal alcohol syndrome, involves facial dysmorphism, growth deficits, and neurocognitive problems. The classic facial characteristics include short palpebral fissures, smooth philtrum, and thin upper vermillion. WHAT THIS STUDY ADDS:This study develops novel strategies to help detect facial dysmorphism across the fetal alcohol spectrum, especially in children with heavy alcohol exposure but without classic facial characteristics. The methods show potential for identifying which of these children are cognitively affected. abstract OBJECTIVE: Classic facial characteristics of fetal alcohol syndrome (FAS) are shortened palpebral fissures, smooth philtrum, and thin upper vermillion. We aim to help pediatricians detect facial dysmorphism across the fetal alcohol spectrum, especially among nonsyndromal heavily exposed (HE) individuals without classic facial characteristics. METHODS:Of 192 Cape Coloured children recruited, 69 were born to women who reported abstaining from alcohol during pregnancy. According to multifaceted criteria, the remainder were allocated clinically to the FAS (n = 22), partial FAS (n = 26) or nonsyndromal HE (n = 75) categories. We used dense surface modeling and signature analyses of 3-dimensional facial photographs to determine agreement between clinical categorization and classifications induced from face shape alone, to visualize facial differences, and to consider predictive links between face shape and neurobehavior.RESULTS: Face classification achieved significant agreement with clinical categories for discrimination of nonexposed from FAS alone (face: 0.97-1.00; profile: 0.92) or with the addition of partial FAS (face: 0.90; profile: 0.92). Visualizations of face signatures delineated dysmorphism across the fetal alcohol spectrum and in half of the nonsyndromal HE category face signature graphs detected facial characteristics consistent with prenatal alcohol exposure. This subgroup performed less well on IQ and learning tests than did nonsyndromal subjects without classic facial characteristics.CONCLUSIONS: Heat maps and morphing visualizations of face signatures may help clinicians detect facial dysmorphism across the fetal alcohol spectrum. Face signature graphs show potential for identifying nonsyndromal heavily exposed children who lack the classic facial phenotype but have cognitive impairment. Pediatrics 2013;131:e779-e788 AUTHORS:

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The face signature of fibrodysplasia ossificans progressiva

Cited by 41 publications

References 34 publications

Fibrodysplasia Ossificans Progressiva: Clinical Course, Genetic Mutations and Genotype-Phenotype Correlation

Fibrodysplasia Ossificans Progressiva: Clinical Course, Genetic Mutations and Genotype-Phenotype Correlation

Craniofacial characteristics of fragile X syndrome in mouse and man

Facial Dysmorphism Across the Fetal Alcohol Spectrum

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