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Genetic risk factors help increase the accuracy of fracture prediction in postmenopausal women
DOI:10.1038/bonekey.2014.40
Physicians assesses fracture risk in osteoporotic postmenopausal women using clinical risk factors combined with bone mineral density (BMD) measurements, but genetic factors are not taken into account. Hun Lee et al. studied 1229 Korean women to find out whether adding genetic profiling could help improve the accuracy of fracture predictions overall and for specific fracture types.
A total of 21 single-nucleotide polymorphisms in 19 separate loci within the human genome were chosen for inclusion in the genetic profile. The value of five different prediction models was then determined. These were genetic risk factors only (I), BMD only (II), clinical risk factors only (III), clinical risk factors and BMD (IV) and all three (BMD+clinical risk factors+genetic risk factors: V).
The score determined by genetic risk factors only was associated with BMD at the neck of the femur and at the lumbar spine before and after adjustment for other factors, including age, height and weight. This genetic score was also associated with fracture risk (any fracture and nonvertebral fracture alone). When model V was compared to model IV, a gain in accuracy of 12.3% was seen for women with nonvertebral fractures, which is statistically significant (P=0.014).
Editor’s comment: Current methods of predicting fracture risk in postmenopausal women would be improved if genetic risk factors were taken into account. By this, clinicians might enhance the accuracy of bone fracture predictions and identify patients who require earlier intervention.
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