Limited Clinical Utility of a Genetic Risk Score for the Prediction of Fracture Risk in Elderly Subjects

  • Joel Eriksson
    Centre for Bone and Arthritis Research, Institute of MedicineSahlgrenska Academy, University of GothenburgGothenburgSweden
  • Daniel S Evans
    Research InstituteCalifornia Pacific Medical CenterSan FranciscoCAUSA
  • Carrie M Nielson
    Public Health and Preventive MedicineOregon Health and Science UniversityPortlandORUSA
  • Jian Shen
    Department of Medicine, Bone and Mineral UnitOregon Health and Science UniversityPortlandORUSA
  • Priya Srikanth
    Public Health and Preventive MedicineOregon Health and Science UniversityPortlandORUSA
  • Marc Hochberg
    Departments of Medicine, Epidemiology, and Preventive MedicineUniversity of Maryland School of MedicineBaltimoreMDUSA
  • Shannon McWeeney
    Oregon Clinical and Translational Research InstituteOregon Health and Science UniversityPortlandORUSA
  • Peggy M Cawthon
    San Francisco Coordinating CenterCalifornia Pacific Medical CenterSan FranciscoCAUSA
  • Beth Wilmot
    Department of Medical Informatics and Clinical EpidemiologyOregon Health and Science UniversityPortlandORUSA
  • Joseph Zmuda
    Department of Epidemiology, Graduate School of Public HealthUniversity of PittsburghPittsburghPAUSA
  • Greg Tranah
    Research InstituteCalifornia Pacific Medical CenterSan FranciscoCAUSA
  • Daniel B Mirel
    Program in Medical and Population GeneticsBroad InstituteCambridgeMAUSA
  • Sashi Challa
    Oregon Clinical and Translational Research InstituteOregon Health and Science UniversityPortlandORUSA
  • Michael Mooney
    Department of Medical Informatics and Clinical EpidemiologyOregon Health and Science UniversityPortlandORUSA
  • Andrew Crenshaw
    Broad Institute of MIT and HarvardCambridgeMAUSA
  • Magnus Karlsson
    Clinical and Molecular Osteoporosis Research UnitDepartment of Clinical Sciences, Lund UniversityMalmöSweden
  • Dan Mellström
    Centre for Bone and Arthritis Research, Institute of MedicineSahlgrenska Academy, University of GothenburgGothenburgSweden
  • Liesbeth Vandenput
    Centre for Bone and Arthritis Research, Institute of MedicineSahlgrenska Academy, University of GothenburgGothenburgSweden
  • Eric Orwoll
    Department of Medicine, Bone and Mineral UnitOregon Health and Science UniversityPortlandORUSA
  • Claes Ohlsson
    Centre for Bone and Arthritis Research, Institute of MedicineSahlgrenska Academy, University of GothenburgGothenburgSweden

抄録

<jats:title>ABSTRACT</jats:title> <jats:sec> <jats:title> </jats:title> <jats:p>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. © 2014 American Society for Bone and Mineral Research.</jats:p> </jats:sec>

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