Cortical bone loss is an early feature of nonradiographic axial spondyloarthritis

Abstract

BackgroundIn the present study, we investigated bone geometry, microstructure, and volumetric bone mineral density (vBMD) in a cohort of patients with nonradiographic axial spondyloarthritis (nr-axSpA) in order to define the early bone changes occurring in axial spondyloarthritis (axSpA) and to define potential factors for deterioration of bone microstructure.MethodsPatients with axSpA (n = 107) and healthy control subjects (n = 50) of similar age and sex were assessed for geometric, volumetric, and microstructural parameters of bone using high-resolution peripheral quantitative computed tomography (HR-pQCT) at the radius. Additionally, demographic and disease-specific characteristics of patients with axSpA were recorded.ResultsPatients with nr-axSpA and control subjects were comparable in age, sex, and body mass index. Geometric and microstructural analysis by HR-pQCT revealed a significantly reduced cortical area (p = 0.022) and cortical thickness (p = 0.006) in patients with nr-axSpA compared with control subjects. Total and cortical vBMD were significantly reduced in patients with nr-axSpA (p = 0.042 and p = 0.007, respectively), whereas there was no difference in trabecular vBMD. Patients with a short disease duration (< 2 years; n = 46) also showed significant reduction of cortical thickness and cortical area compared with control subjects. Patients with disease duration > 2 years (n = 55) additionally developed a decrease of cortical and total vBMD. Multiple regression models identified male sex to be associated with lower cortical vBMD and female sex to be associated with lower trabecular vBMD.ConclusionsBone microstructure in patients with nr-axSpA is characterized primarily by deterioration of cortical bone. Cortical bone loss starts early and is evident within the first 2 years of the disease.Electronic supplementary materialThe online version of this article (10.1186/s13075-018-1620-1) contains supplementary material, which is available to authorized users.

Osteoporosis in Rheumatic Diseases

“…Unsurprisingly, the parameters of systemic inflammation (i.e., increase in the C-reactive protein) have also been associated with low BMD [107]. The role of systemic inflammation as a determinant for generalized bone loss is also supported by the demonstration of low cortical BMD, and the area and thickness measured by HRpQCT [118]; once again, this process was reported as an early event.…”

A Contemporary View of the Diagnosis of Osteoporosis in Patients With Axial Spondyloarthritis

“…In another study by Neumann et al, HR-pQCT showed pronounced bone loss in the cortical area, cortical thickness, and cortical BMD in patients with nr-axSpA as compared to controls. However, trabecular vBMD did not differ between patients and controls (81). Patients with short disease duration (<2 years) also showed a significant reduction in cortical thickness and cortical area when compared with controls, and the decrease in cortical thickness was more prominent in long-term patients (disease duration >2 years).…”

“…HR-pQCT measures the trabecular and cortical compartments separately at the tibia and radius, allowing measurement of large portions of distal bones with good spatial resolution and minimal irradiation (16,17). HR-pQCT measures microarchitecture parameters such as trabecular thickness, number and distribution, and cortical porosity of the tibia and radius, thus resembling a virtual bone biopsy of the peripheral bone (16,79,81,82). It was previously argued that osteoporosis in patients with axSpA primarily affects the axial skeleton (23,83).…”

Quantitative Imaging in Inflammatory Arthritis: Between Tradition and Innovation

“…46 According to the results of Neumann et al, the use of this tool could become crucial for diagnosing early changes in patients with nonradiographic AS because it can detect cortical deterioration that occurs within the first 2 years of the disease. 47 Like DEXA, HR-pQCT can also be used to investigate lean mass by dedicated software separating fat, muscles, and bones and selecting appropriate density thresholds on a single slice of interest. Parameters like muscle cross-sectional area, muscle density, and intramuscular adipose tissue area can then be collected.…”