Genetic profiling and individualized prognosis of fracture

Tran, BN; Nguyen, ND; Nguyen, VX; Center, JR; Eisman, JA; Nguyen, TV

Genetic profiling and individualized prognosis of fracture

Tran, BN Nguyen, ND Nguyen, VX Center, JR Eisman, JA Nguyen, TV

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Publication Type:: Journal Article
Citation:: Journal of Bone and Mineral Research, 2011, 26 (2), pp. 414 - 419
Issue Date:: 2011-02-01

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Field	Value	Language
dc.contributor.author	Tran, BN	en_US
dc.contributor.author	Nguyen, ND	en_US
dc.contributor.author	Nguyen, VX	en_US
dc.contributor.author	Center, JR	en_US
dc.contributor.author	Eisman, JA	en_US
dc.contributor.author	Nguyen, TV https://orcid.org/0000-0002-3246-6281	en_US
dc.date.issued	2011-02-01	en_US
dc.identifier.citation	Journal of Bone and Mineral Research, 2011, 26 (2), pp. 414 - 419	en_US
dc.identifier.issn	0884-0431	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28785
dc.description.abstract	Fragility fracture is a serious public health problem in the world. The risk of fracture is determined by genetic and nongenetic clinical risk factors. This study sought to quantify the contribution of genetic profiling to fracture prognosis. The study was built on the ongoing Dubbo Osteoporosis Epidemiology Study, in which fracture and risk factors of 858 men and 1358 women had been monitored continuously from 1989 and 2008. Fragility fracture was ascertained by radiologic reports. Bone mineral density at the femoral neck was measured by dual-energy X-ray absorptiometry (DXA). Fifty independent genes with allele frequencies ranging from 0.01 to 0.60 and relative risks (RRs) ranging from 1.01 to 3.0 were simulated. Three predictive models were fitted to the data in which fracture was a function of (1) clinical risk factors only, (2) genes only, and (3) clinical risk factors and 50 genes. The area under the curve (AUC) for model 1 was 0.77, which was lower than that of model II (AUC=0.82). Adding genes into the clinical risk factors model (model 3) increased the AUC to 0.88 and improved the accuracy of fracture classification by 45%, with most (41%) improvement in specificity. In the presence of clinical risk factors, the number of genes required to achieve an AUC of 0.85 was around 25. These results suggest that genetic profiling could enhance the predictive accuracy of fracture prognosis and help to identify high-risk individuals for appropriate management of osteoporosis or intervention. © 2011 American Society for Bone and Mineral Research.	en_US
dc.relation.ispartof	Journal of Bone and Mineral Research	en_US
dc.relation.isbasedon	10.1002/jbmr.219	en_US
dc.subject.classification	Anatomy & Morphology	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Osteoporosis	en_US
dc.subject.mesh	Absorptiometry, Photon	en_US
dc.subject.mesh	Prognosis	en_US
dc.subject.mesh	Area Under Curve	en_US
dc.subject.mesh	Risk	en_US
dc.subject.mesh	Risk Factors	en_US
dc.subject.mesh	Gene Expression Profiling	en_US
dc.subject.mesh	Fracture Healing	en_US
dc.subject.mesh	Bone Density	en_US
dc.subject.mesh	Aged	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Fractures, Bone	en_US
dc.title	Genetic profiling and individualized prognosis of fracture	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	26	en_US
utslib.for	0903 Biomedical Engineering	en_US
utslib.for	1103 Clinical Sciences	en_US
utslib.for	06 Biological Sciences	en_US
utslib.for	09 Engineering	en_US
utslib.for	11 Medical and Health Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	26	en_US

Abstract:

Fragility fracture is a serious public health problem in the world. The risk of fracture is determined by genetic and nongenetic clinical risk factors. This study sought to quantify the contribution of genetic profiling to fracture prognosis. The study was built on the ongoing Dubbo Osteoporosis Epidemiology Study, in which fracture and risk factors of 858 men and 1358 women had been monitored continuously from 1989 and 2008. Fragility fracture was ascertained by radiologic reports. Bone mineral density at the femoral neck was measured by dual-energy X-ray absorptiometry (DXA). Fifty independent genes with allele frequencies ranging from 0.01 to 0.60 and relative risks (RRs) ranging from 1.01 to 3.0 were simulated. Three predictive models were fitted to the data in which fracture was a function of (1) clinical risk factors only, (2) genes only, and (3) clinical risk factors and 50 genes. The area under the curve (AUC) for model 1 was 0.77, which was lower than that of model II (AUC=0.82). Adding genes into the clinical risk factors model (model 3) increased the AUC to 0.88 and improved the accuracy of fracture classification by 45%, with most (41%) improvement in specificity. In the presence of clinical risk factors, the number of genes required to achieve an AUC of 0.85 was around 25. These results suggest that genetic profiling could enhance the predictive accuracy of fracture prognosis and help to identify high-risk individuals for appropriate management of osteoporosis or intervention. © 2011 American Society for Bone and Mineral Research.

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http://hdl.handle.net/10453/28785