AI Article Synopsis

  • Identifying high-risk fracture patients is critical, with a study linking genetic factors (63 SNPs) to bone mineral density (BMD) and fracture risk, leading to the creation of two genetic risk scores (GRS63 and GRS16).
  • While GRS63 showed some association with BMD, it did not correlate with changes in BMD; both GRSs were linked to fracture risk but had reduced effectiveness after adjusting for BMD.
  • The addition of these genetic risk scores provided only minor improvements in predictive models, indicating their limited clinical utility for predicting fractures in elderly individuals when BMD is already considered.

Article Abstract

It is important to identify the patients at highest risk of fractures. A recent large-scale meta-analysis identified 63 autosomal single-nucleotide polymorphisms (SNPs) associated with bone mineral density (BMD), of which 16 were also associated with fracture risk. Based on these findings, two genetic risk scores (GRS63 and GRS16) were developed. Our aim was to determine the clinical usefulness of these GRSs for the prediction of BMD, BMD change, and fracture risk in elderly subjects. We studied two male (Osteoporotic Fractures in Men Study [MrOS] US, MrOS Sweden) and one female (Study of Osteoporotic Fractures [SOF]) large prospective cohorts of older subjects, looking at BMD, BMD change, and radiographically and/or medically confirmed incident fractures (8067 subjects, 2185 incident nonvertebral or vertebral fractures). GRS63 was associated with BMD (≅3% of the variation explained) but not with BMD change. Both GRS63 and GRS16 were associated with fractures. After BMD adjustment, the effect sizes for these associations were substantially reduced. Similar results were found using an unweighted GRS63 and an unweighted GRS16 compared with those found using the corresponding weighted risk scores. Only minor improvements in C-statistics (AUC) for fractures were found when the GRSs were added to a base model (age, weight, and height), and no significant improvements in C-statistics were found when they were added to a model further adjusted for BMD. Net reclassification improvements with the addition of the GRSs to a base model were modest and substantially attenuated in BMD-adjusted models. GRS63 is associated with BMD, but not BMD change, suggesting that the genetic determinants of BMD differ from those of BMD change. When BMD is known, the clinical utility of the two GRSs for fracture prediction is limited in elderly subjects.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4281709PMC
http://dx.doi.org/10.1002/jbmr.2314DOI Listing

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