We propose a novel approach for identifying skeletal trait patterns that predict fracture risk in older men and
women, independent of areal bone mineral density (aBMD). The breakthrough was finding that aBMD loss
results from different relative proportions of decline in bone mineral content (BMC) and increase in bone area
based on baseline external bone size. aBMD is often used as a surrogate of strength, and loss in aBMD is often
assumed to reflect loss in strength. However, this association has been predicated on an implicit assumption
that the proportion of BMC-declines to area-increases is similar among individuals which our data contradict. In
the proposed work, we will test the global hypothesis that external bone size is associated with variation in
strength-decline trajectory and fracture risk, independent of aBMD. This hypothesis is supported by preliminary
cadaveric studies showing different strength-age regressions for narrow and wide subgroups. Moreover, we
show that low aBMD may explain fracture risk within subgroups stratified by external bone size but did not explain
the two-fold increase in fracture risk between subgroups. Thus, we have identified limitations in the uniform
application of aBMD to predict fracture risk, suggesting that recognizing population heterogeneity is necessary
for advancing fracture risk prediction. To address these limitations, we will identify the structural traits that explain
fracture risk within subgroups and test the hypothesis that the structural traits predicting fracture risk differ among
the subgroups. We first leverage high resolution imaging and direct mechanical tests available for cadaveric
femurs to test the hypothesis that the structural trait patterns determining low femur strength vary with external
femur size (Aim 1). To systematically identify structural patterns associated with variation in fracture risk and
strength-decline trajectories, we will use statistical shape and trait modeling within a novel computational
framework to identify the specific structural patterns that best predict experimental strength and then test how
these associations differ with external size, sex, and race. We address how these structure-function relationships
change over time by leveraging existing longitudinal hip DXA data for elderly White men enrolled in the
Osteoporotic Fractures in Men Study (MrOS) and elderly White women enrolled in Health ABC (Aim 2) and
elderly Black men and women enrolled in Health ABC (Aim 3). We will test the hypothesis that strength-decline
trajectories differ between baseline FN area tertiles for older men and women, and that the strength-trajectory is
associated with risk of fracture within tertiles. Successful completion of these aims will provide evidence of
multiple biomechanical pathways leading to reduced proximal femur strength in older men and women and will
identify sets of traits and trait interactions that best predict fracture risk for subgroups of individuals. This outcome
will explain why changes in aBMD track strength-decline for some but not all individuals, and will identify early
indicators of fragility fractures, providing a voice to what has been called a silent disease.