Cluster analysis of bone microarchitecture from high resolution peripheral quantitative computed tomography demonstrates two separate phenotypes associated with high fracture risk in men and women

Highlights

• Prevalent fracture is associated with lower cortical thickness in both men and women

• Two distinct bone phenotypes have been identified with elevated fracture prevalence

• Men with bones with large cross-section and thin cortex were at higher risk of prevalent fracture

Abstract

Osteoporosis is a major healthcare problem which is conventionally assessed by dual energy X-ray absorptiometry (DXA). New technologies such as high resolution peripheral quantitative computed tomography (HRpQCT) also predict fracture risk. HRpQCT measures a number of bone characteristics that may inform specific patterns of bone deficits. We used cluster analysis to define different bone phenotypes and their relationships to fracture prevalence and areal bone mineral density (BMD). 177 men and 159 women, in whom fracture history was determined by self-report and vertebral fracture assessment, underwent HRpQCT of the distal radius and femoral neck DXA. Five clusters were derived with two clusters associated with elevated fracture risk. “Cluster 1” contained 26 women (50.0% fractured) and 30 men (50.0% fractured) with a lower mean cortical thickness and cortical volumetric BMD, and in men only, a mean total and trabecular area more than the sex-specific cohort mean. “Cluster 2” contained 20 women (50.0% fractured) and 14 men (35.7% fractured) with a lower mean trabecular density and trabecular number than the sex-specific cohort mean. Logistic regression showed fracture rates in these clusters to be significantly higher than the lowest fracture risk cluster [5] (p < 0.05). Mean femoral neck areal BMD was significantly lower than cluster 5 in women in cluster 1 and 2 (p < 0.001 for both), and in men, in cluster 2 (p < 0.001) but not 1 (p = 0.220). In conclusion, this study demonstrates two distinct high risk clusters in both men and women which may differ in etiology and response to treatment. As cluster 1 in men does not have low areal BMD, these men may not be identified as high risk by conventional DXA alone.

Introduction

Osteoporosis is a significant global health problem with around one in two women and one in five men over the age of 50 expected to experience an osteoporotic fracture in their lifetime [1]. These can cause significant disability, morbidity and even mortality along with a considerable economic cost of both inpatient and community care services [2]. In clinical practice, osteoporosis is diagnosed using dual energy X-ray absorptiometry (DXA) of the hip and lumbar spine. This also has a role in fracture prediction as it has been shown that there is an approximate doubling of risk for every one standard deviation (SD) reduction in areal bone mineral density (BMD) [3]. However, it is recognized that the basis of bone fragility is heterogeneous. To group individuals into one seemingly homogeneous group because of a T score below − 2.5, one or more spine fractures, or a low trauma hip fracture, would obscure the heterogeneity in structural, cellular, and biomechanical basis of bone fragility [4].

Assessment by DXA does not measure volumetric BMD, does not differentiate between cortical and trabecular compartments, and does not provide measures of bone geometry, all of which might contribute to fracture risk. Recently, cross-sectional imaging techniques, including high resolution peripheral quantitative computed tomography (HRpQCT), have been developed and utilized in a research setting to differentiate fracture cases from those without [5], [6], [7], [8], [9]. To date, most of these studies have been completed in women. So far, they suggest that specific components of bone structure, such as cortical thickness and trabecular microarchitecture, are deficient in fracture cases. It may, however, be more appropriate to explore different bone phenotypes, combining multiple outcomes related to bone strength, and their relationships to fracture.

In this study we aimed to use statistical cluster analysis, based upon mathematical, rather than pre-defined clinical, assumptions to define bone phenotypes for men and women taking into account all parameters measured by HRpQCT. We then determined whether the data-driven clusters were associated with different rates of fracture occurrence. Additionally, we assessed whether cluster phenotypes with high fracture prevalence had a corresponding low areal BMD as assessed by DXA.