Bone Material Properties in Osteogenesis Imperfecta

Bishop, Nick

doi:10.1002/jbmr.2835

Cited by 69 publications

(52 citation statements)

References 138 publications

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“…While bmp1a -/-and plod2 -/-mutants exhibited differing effects on indices of bone mass and microarchitecture, both mutants exhibited high TMD. This phenotype is consistent with the bone over-mineralization that is a hallmark of brittle bone disease (Bishop, 2016). While bmp1a -/-mutants exhibit increased TMD in all vertebral compartments (centrum, haemal arch, and neural arch), plod2 -/-fish exhibit high TMD in the centrum only.…”

Section: Discussionsupporting

confidence: 79%

MicroCT-Based Phenomics in the Zebrafish Skeleton Reveals Virtues of Deep Phenotyping in a Distributed Organ System

et al. 2018

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Phenomics, which ideally involves in-depth phenotyping at the whole-organism scale, may enhance our functional understanding of genetic variation. Here, we demonstrate methods to profile hundreds of phenotypic measures comprised of morphological and densitometric traits at a large number of sites within the axial skeleton of adult zebrafish. We show the potential for vertebral patterns to confer heightened sensitivity, with similar specificity, in discriminating mutant populations compared to analyzing individual vertebrae in isolation. We identify phenotypes associated with human brittle bone disease and thyroid stimulating hormone receptor hyperactivity. Finally, we develop allometric models and show their potential to aid in the discrimination of mutant phenotypes masked by alterations in growth. Our studies demonstrate virtues of deep phenotyping in a spatially distributed organ system. Analyzing phenotypic patterns may increase productivity in genetic screens, and facilitate the study of genetic variants associated with smaller effect sizes, such as those that underlie complex diseases.

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Section: Discussionsupporting

confidence: 79%

MicroCT-Based Phenomics in the Zebrafish Skeleton Reveals Virtues of Deep Phenotyping in a Distributed Organ System

et al. 2018

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“…Last, this is in good agreement with the increased amount of mineral in the matrix, corresponding to a higher density of thinner mineral platelets in both oim mouse mod els 124,127 and patients with osteogenesis imperfecta 120 . The cooperative effect of these secondary defects on bone fragility is probably more important than the collagen mutation itself, as discussed in a recent review 133 .…”

Section: Box 2 | Ehlers-danlos Syndromementioning

confidence: 99%

“…Most crucially, bone in osteogenesis imperfecta is a brittle tissue and cannot dissipate energy efficiently; although healthy bone can absorb energy into the extracellular matrix with advanc ing deformation, osteogenesis imperfecta bone snaps like chalk with minimal displacement 133 .…”

Section: Box 2 | Ehlers-danlos Syndromementioning

confidence: 99%

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Osteogenesis imperfecta

Marini

Forlino

Bächinger

et al. 2017

Nat Rev Dis Primers

504

582

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| Skeletal deformity and bone fragility are the hallmarks of the brittle bone dysplasia osteogenesis imperfecta. The diagnosis of osteogenesis imperfecta usually depends on family history and clinical presentation characterized by a fracture (or fractures) during the prenatal period, at birth or in early childhood; genetic tests can confirm diagnosis. Osteogenesis imperfecta is caused by dominant autosomal mutations in the type I collagen coding genes (COL1A1 and COL1A2) in about 85% of individuals, affecting collagen quantity or structure. In the past decade, (mostly) recessive, dominant and X-linked defects in a wide variety of genes encoding proteins involved in type I collagen synthesis, processing, secretion and post-translational modification, as well as in proteins that regulate the differentiation and activity of bone-forming cells have been shown to cause osteogenesis imperfecta. The large number of causative genes has complicated the classic classification of the disease, and although a new genetic classification system is widely used, it is still debated. Phenotypic manifestations in many organs, in addition to bone, are reported, such as abnormalities in the cardiovascular and pulmonary systems, skin fragility, muscle weakness, hearing loss and dentinogenesis imperfecta. Management involves surgical and medical treatment of skeletal abnormalities, and treatment of other complications. More innovative approaches based on gene and cell therapy, and signalling pathway alterations, are under investigation. NATURE REVIEWS | DISEASE PRIMERS VOLUME 3 | ARTICLE NUMBER 17052 | 1 PRIMER © 2 0 1 7 M a c m i l l a n P u b l i s h e r s L i m i t e d , p a r t o f S p r i n g e r N a t u r e . A l l r i g h t s r e s e r v e d .In this Primer, we provide an overview of epidemio logy, genetics and pathophysiology of osteogenesis imperfecta, as well as diagnosis and management. EpidemiologyStudies from Europe and the United States have found a birth prevalence of osteogenesis imperfecta of 0.3-0.7 per 10,000 births 5,6 . These birth cohort analyses reflect more severe types of osteogenesis imperfecta and do not include more subtle types that become apparent after birth. A population based study that used the Danish National Patient Register found an annual incidence of osteogenesis imperfecta of 1.5 per 10,000 births between 1997 and 2013 (REF. 7). Population surveys in countries with comprehensive medical databases, such as Finland, estimated a prevalence of about 0.5 per 10,000 individ uals 8 , with most having phenotypically milder osteo genesis imperfecta type I and type IV (BOX 1; TABLE 1). Because these birth cohort and population surveys are based on clinical findings and tend to find mutu ally exclusive populations, a reasonable estimate of the incidence of osteogenesis imperfecta is about 1 per 10,000 individuals. Most patients are heterozygous for mutations in COL1A1 or COL1A2. No difference in the prevalence between sexes was reported.Approximately 90% of the 3,000 individuals whose mutations ha...

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“…Since the overall fracture resistance of bone arises from each level of its organizational hierarchy 1,2 , numerous changes at multiple length-scales can contribute to an age- or disease-related increase in fracture risk. The relative contribution of changes in composition and organization of the matrix to this increase is difficult to assess, but in general, the bone matrix is an important contributor to fracture resistance as suggested by mouse models in which the deletion of matrix genes cause low bone toughness 3–5 or by genetic mutations affecting collagen I structure such as osteogenesis imperfecta, a brittle bone disease 6,7 . Presently, in vivo assessment of sub-microstructural features of bone composition and matrix organization as indicators of bone fragility is still in the developmental stage.…”

Section: Introductionmentioning

confidence: 99%

Applying Full Spectrum Analysis to a Raman Spectroscopic Assessment of Fracture Toughness of Human Cortical Bone

et al. 2017

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A decline in the inherent quality of bone tissue is a contributor to the age-related increase in fracture risk. Although this is well known, the important biochemical factors of bone quality have yet to be identified using Raman spectroscopy (RS), a non-destructive, inelastic light scattering technique. To identify potential RS predictors of fracture risk, we applied principal component analysis (PCA) to 558 Raman spectra (370 cm−1 – 1720 cm−1) of human cortical bone acquired from 62 female and male donors (9 spectra each) spanning adulthood (21 – 101 yo). Spectra were analyzed prior to R-curve, non-linear fracture mechanics that delineates crack initiation (Kinit) from crack growth toughness (Kgrow). The traditional ν1Phosphate peak per Amide I peak (mineral-to-matrix ratio) weakly correlated with Kinit (r = 0.341, p =0.0067) and overall crack growth toughness (J-int: r = 0.331, p =0.0086). Sub-peak ratios of the Amide I band that are related to the secondary structure of type 1 collagen did not correlate with the fracture toughness properties. In the full spectrum analysis, one principal component (PC5) correlated with all of the mechanical properties (Kinit: r = −0.467, Kgrow: r = −0.375, and J-int: r = −0.428; p < 0.0067). More importantly, when known predictors of fracture toughness, namely age and/or volumetric bone mineral density (vBMD), were included in general linear models as covariates, several principal components helped explain 45.0% (PC5) to 48.5% (PC7), 31.4% (PC6), and 25.8% (PC7) of the variance in Kinit, Kgrow, and J-int, respectively. Deriving spectral features from full spectrum analysis may improve the ability of RS, a clinically viable technology, to assess fracture risk.

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Bone Material Properties in Osteogenesis Imperfecta

Cited by 69 publications

References 138 publications

MicroCT-Based Phenomics in the Zebrafish Skeleton Reveals Virtues of Deep Phenotyping in a Distributed Organ System

MicroCT-Based Phenomics in the Zebrafish Skeleton Reveals Virtues of Deep Phenotyping in a Distributed Organ System

Osteogenesis imperfecta

Applying Full Spectrum Analysis to a Raman Spectroscopic Assessment of Fracture Toughness of Human Cortical Bone

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