External Bone Size Is a Key Determinant of Strength-Decline Trajectories of Aging Male Radii

Abstract

Given prior work showing associations between remodeling and external bone size, we tested the hypothesis that wide bones would show a greater negative correlation between whole-bone strength and age compared with narrow bones. Cadaveric male radii (n = 37 pairs, 18 to 89 years old) were evaluated biomechanically, and samples were sorted into narrow and wide subgroups using height-adjusted robustness (total area/bone length). Strength was 54% greater (p < 0.0001) in wide compared with narrow radii for young adults (<40 years old). However, the greater strength of young-adult wide radii was not observed for older wide radii, as the wide (R² = 0.565, p = 0.001), but not narrow (R² = 0.0004, p = 0.944) subgroup showed a significant negative correlation between strength and age. Significant positive correlations between age and robustness (R² = 0.269, p = 0.048), cortical area (Ct.Ar; R² = 0.356, p = 0.019), and the mineral/matrix ratio (MMR; R² = 0.293, p = 0.037) were observed for narrow, but not wide radii (robustness: R² = 0.015, p = 0.217; Ct.Ar: R² = 0.095, p = 0.245; MMR: R² = 0.086, p = 0.271). Porosity increased with age for the narrow (R² = 0.556, p = 0.001) and wide (R² = 0.321, p = 0.022) subgroups. The wide subgroup (p < 0.0001) showed a significantly greater elevation of a new measure called the Cortical Pore Score, which quantifies the cumulative effect of pore size and location, indicating that porosity had a more deleterious effect on strength for wide compared with narrow radii. Thus, the divergent strength-age regressions implied that narrow radii maintained a low strength with aging by increasing external size and mineral content to mechanically offset increases in porosity. In contrast, the significant negative strength-age correlation for wide radii implied that the deleterious effect of greater porosity further from the centroid was not offset by changes in outer bone size or mineral content. Thus, the low strength of elderly male radii arose through different biomechanical mechanisms. Consideration of different strength-age regressions (trajectories) may inform clinical decisions on how best to treat individuals to reduce fracture risk. © 2019 American Society for Bone and Mineral Research.

Keywords: AGING; BIOMECHANICAL MECHANISMS; BIOMECHANICS; BONE; MALE; PERIOSTEAL EXPANSION; RADII; STRENGTH.

Fig. 1.

(A) Schematic illustrating the two ways that the Cortical Pore Score was calculated from the nanoCT images (left: CPS_plane, right: CPS_point). Inset illustrates how voids adjacent to the marrow space were manually closed so they were included in the porosity analysis (arrows). (B) The flow chart shows known associations between physical bone traits and whole-bone strength. These associations helped inform decisions on the selection of traits used in the multivariate regression analysis and for establishing the biomechanical pathways responsible for different strength-decline trajectories. The flow chart shows three trait categories that contribute to bone strength. These include whole-bone mechanical properties, morphology, and tissue-level mechanical properties. The wide borders indicate the traits used in the multivariate regression analysis.

Fig. 2.

(A) A nonsignificant association was found between maximum bending moment (whole-bone strength) and age when all the data were included in a single regression. (B) Sorting the data based on height-adjusted robustness (excluding middle 3 rank-ordered subjects per subgroup) showed a significant association for wide but not narrow radii and a significant difference between the slopes of the two regressions (ANCOVA).

Fig. 3.

Linear regressions between (A) robustness, (B) cortical area, (C) marrow area, (D) moment of inertia (I_ML) and age differed between the narrow and wide subgroups.

Fig. 4.

Linear regressions between (A) overall porosity and age, (B) midcortical porosity and age, (C) average pore area and age, (D) CPS_plane and overall porosity, (E) CPS_plane and age, and (F) CPS_plane/I_MLfilled and age for the narrow and wide subgroups.

Fig. 5.

Linear regressions between (A) collagen disorder/order ratio, (B) lipid/matrix ratio, (C) mineral/matrix ratio (MMR), (D) hydroxyproline/proline (hyp/pro) ratio, (E) collagen crosslinks (Xlinks) ratio, and (F) mineral crystallinity and age for the narrow and wide subgroups.

Fig. 6.

Linear regressions between (A) tissue-modulus, (B) tissue-strength, (C) tissue postyield strain, (D) tissue energy-to-failure and age for the narrow and wide subgroups.

Fig. 7.

Schematic illustrating the different structural and material changes contributing to the biomechanical mechanisms that help explain the different strength–age regressions between narrow and wide subgroups.