Osteoporosis and Bone Biology Program, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Sydney, NSW 2010, Australia.
Curr Osteoporos Rep. 2012 Sep;10(3):236-44. doi: 10.1007/s11914-012-0113-4.
Recent genome-wide association studies have identified many genetic variants associated with fracture risk. These genetic variants are common in the general population but have very modest effect sizes. A remaining challenge is to translate these genetic variant discoveries to better predict the risk of fracture based on an individual's genetic profile (ie, individualized risk assessment). Empirical and simulation studies have shown that 1) the utility of a single genetic variant for fracture risk assessment is very limited; but 2) a profile of 50 genetic variants, each with odds ratio ranging from 1.02 to 1.15, can improve the accuracy of fracture prediction and classification beyond that obtained by conventional clinical risk factors. These results are consistent with the view that genetic profiling, when integrated in existing risk assessment models, can inform a more accurate prediction of fracture risk in an individual.
最近的全基因组关联研究已经确定了许多与骨折风险相关的遗传变异。这些遗传变异在普通人群中很常见，但效应大小非常有限。目前面临的挑战是将这些遗传变异发现转化为更好地根据个体的遗传特征预测骨折风险（即个体化风险评估）。实证和模拟研究表明：1）单个遗传变异用于骨折风险评估的效用非常有限；但是 2）50 个遗传变异的特征，每个变异的优势比在 1.02 到 1.15 之间，可以提高骨折预测和分类的准确性，超过传统临床危险因素所获得的准确性。这些结果与遗传特征分析的观点一致，即当整合到现有的风险评估模型中时，遗传特征分析可以更准确地预测个体的骨折风险。
