Variation in childhood skeletal robustness is an important determinant of cortical area in young adults

Abstract

A better understanding of bone growth will benefit efforts to reduce fracture incidence, because variation in elderly bone traits are determined primarily by adulthood. The natural variation in robustness was used as a model to understand how variable growth patterns define adult bone morphology. Longitudinally acquired hand radiographs of 29 boys and 30 girls were obtained from the Bolton-Brush study for 6 time points spanning 8 to 18 years of age. Segregating individuals into tertiles based on robustness revealed that the biological activity underlying bone growth varied significantly with the natural variation in robustness. For boys, slender metacarpals used an osteoblast-dependent growth pattern to establish function, whereas robust metacarpals used an osteoclast-dependent growth pattern. In contrast, differences in biological activity between girls with slender and robust metacarpals were largely based on the age at which the marrow surface changed from expansion to infilling. Importantly, cortical area for slender metacarpals was as much as 19.7% and 32.2% lower than robust metacarpals for boys and girls, respectively, indicating that robustness was a major determinant of adult cortical area. Finally, after accounting for robustness and body weight effects, we found that the inter-individual variation in cortical area was established as early as 8 years of age. While variation in the amount of bone acquired during growth has primarily been attributed to factors like nutrition, exercise, and genetic background, we showed that the natural variation in robustness was also a major determinant of cortical area, which is an important determinant of bone mass. This predictable relationship between robustness and cortical area should be incorporated into clinical diagnostic measures and experimental studies.

Differential Adaptive Response of Growing Bones From Two Female Inbred Mouse Strains to Voluntary Cage‐Wheel Running

“…First, we did not characterize the cellular bone remodeling activity (ie, osteoblasts and osteoblasts) in the femora of mice between the ages of 4 and 8 weeks, which others have shown (40) may vary between inbred mouse strains of the same age. However, the purpose of our study was to examine whether exercise had a differential effect on bone in mice of established phenotypic and genotypic background differences that mirror the variation within bone trait sets observed during growth (41,42) and upon adulthood (37,43) among humans. To convincingly confirm our hypotheses, a similar study is needed using a cohort of children of the same age.…”

Mapping the natural variation in whole bone stiffness and strength across skeletal sites

“…Confirming this association between skeletal elements advocates for the use of the many longitudinal studies, both historic and contemporary, that are consisted of a plethora of hand radiograph data. These databases are ideal for investigating the underlying biology [16,34] as longitudinal studies would define how these interactions develop during growth and how they change with aging.…”

“…individuals with a skeleton comprised of slender bones) is at risk of fracturing despite their bones being as well adapted as biologically possible to maximize stiffness while minimizing mass [15]. Second, cortical area (Ct.Ar) and cortical tissue mineral density (Ct.TMD) naturally vary relative to robustness [9,10,16], resulting in a circumstance wherein variations in Ct.Ar and Ct.TMD are superimposed on the natural variation in robustness. Understanding this variation is important for determining when the covariation between traits is impaired, resulting in reduced fracture resistance.…”

Clinical application of near infrared fiber optic spectroscopy for noninvasive bone assessment

“…Here, we investigate whether NIR spectral data obtained transcutaneously from the second metacarpal (M2) bone, which is covered by only a thin layer of skin and fascia, correlates with bone quality assessed by standard DXA and BHI. Additionally, data from the second metacarpal have been shown to be a significant predictor of fracture risk at the vertebrae and hip , and its robustness has been correlated with that at the tibia and femur . Our goal for the current study was to use cadaver tissues, spectral modeling and data from a cohort of individuals with OI, to assess whether parameters derived from noninvasive NIR spectroscopic bone assessment correlate to standard clinical bone quality parameters, and whether there is potential for use of this nonionizing modality to assess bone quality.…”