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Genetic profiling and individualized assessment of fracture risk

Nature Reviews Endocrinology volume 9, pages 153–161 (2013)Cite this article

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Abstract

Osteoporosis and its consequence of fragility fracture impose a considerable demand on health-care services because fracture is associated with a series of adverse events, including re-fracture and mortality. One of the major priorities in osteoporosis care is the development of predictive models to identify individuals at high risk of fracture for early intervention and management. Existing predictive models include clinical factors and anthropometric characteristics but have not considered genetic variants in the prediction. Genome-wide association studies conducted in the past decade have identified several genetic variants relevant to fracture risk. These genetic variants are common in frequency but have very modest effect sizes. A remaining challenge is to use these genetic data to individualize fracture risk assessment on the basis of an individual's genetic risk profile. Empirical and simulation studies have shown that the usefulness of a single genetic variant for fracture risk assessment is very limited, but a profile of 50 genetic variants, each with odds ratio ranging from 1.02 to 1.15, could improve the accuracy of fracture prediction beyond that obtained by use of existing clinical risk factors. Thus, genetic profiling when integrated with existing risk assessment models could inform a more accurate prediction of fracture risk in an individual.

Key Points

  • Fragility fracture is common in the general population, and is associated with serious consequences, including mortality

  • BMD is the best predictor of fracture risk

  • Interindividual variation in fracture risk is partly determined by genetic factors

  • 62 single nucleotide polymorphisms (SNPs) are associated with BMD in genome-wide association studies; among these SNPs, 18 are associated with fracture risk, of which only eight achieve genome-wide significance level

  • Any single SNP has little predictive value for fracture; however, genetic profiling of 50 SNPs could improve the accuracy of fracture prediction beyond that obtained by existing risk factors

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Figure 1: Odds ratios and 95% confidence intervals for fracture for each of the 32 SNPs identified from genome-wide association study meta-analyses.
Figure 2: The relationship between allelic frequency and odds ratios of 32 SNPs associated with fracture risk identified from genome-wide association study meta-analyses.

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Author information

Authors and Affiliations

  1. Osteoporosis and Bone Biology Program, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Sydney, 2010, NSW, Australia

    Tuan V. Nguyen

  2. Clinical Translation and Advanced Education, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Sydney, 2010, NSW, Australia

    John A. Eisman

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Both authors contributed equally to researching data for the article, discussing the content, writing the manuscript, and reviewing and/or editing the manuscript before submission.

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Correspondence to Tuan V. Nguyen.

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Nguyen, T., Eisman, J. Genetic profiling and individualized assessment of fracture risk. Nat Rev Endocrinol 9, 153–161 (2013). https://doi.org/10.1038/nrendo.2013.3

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