Genetic profiling may improve fracture risk prediction
MedWire News: Genetic profiling could enhance the predictive accuracy of fracture risk assessment and help to identify high-risk individuals for appropriate management of osteoporosis or fracture prevention interventions, according to Australian researchers.
"A major priority in osteoporosis research at present is to develop prognostic models for identifying individuals who have high risk of fracture," say Tuan Nguyen (Garvan Institute of Medical Research, Sydney) and colleagues.
The researchers therefore investigated the contribution of genetic profiling to fracture risk assessment in light of the fact that previous researchers have shown genetic factors account for 25% to 35% of the variance in the liability to fracture.
They tested three fracture prediction models: model 1 included only clinical risk factors such as gender, bone mineral density, and fracture history; model 2 included only genetic profiling data from 50 simulated genes; and model 3 included both clinical risk factors and genetic profiling.
The researchers obtained the clinical data from 2216 participants (61% women) of the Dubbo Osteoporosis Epidemiology Study, in which fracture incidence and risk factors had been monitored continuously from 1989 to 2008.
The 50 simulated genes were created with an assumed allele frequency between 1% and 60% and a relative risk for fracture between 1.1 and 3.0.
Nguyen and team report that the area under the receiver operating characteristic curve (AUC), was 0.77 for model 1 and 0.82 for model 2, indicating that the clinical and genetic models correctly identified patients who would sustain a fracture in 77% and 82% of cases, respectively.
Adding gene profiling to the clinical risk factors (model 3) increased the AUC to 0.88.
The researchers note that the contribution of individual genes to fracture prognosis was small. "Indeed, even for a gene conferring a relative risk of 3.0, the AUC attributable to this gene is barely 0.51," they say.
However, the integration of genetic profiling of multiple genes into the current prognostic models could improve the predictive accuracy of fracture risk significantly for an individual, Nguyen and team add.
They calculated that, in the presence of clinical risk factors for fracture, the number of genes required to achieve an AUC of 0.85 - indicative of clinical usefulness - was around 25.
"Given the ongoing progress of finding new genes for osteoporosis, the prospect of using genetic profiles in the prognosis of fracture is a real possibility," the researchers conclude in the Journal of Bone and Mineral Research.
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By Laura Dean