TY - JOUR
T1 - Bone, muscle, and physical activity
T2 - Structural equation modeling of relationships and genetic influence with age
AU - Lang, Dean H.
AU - Conroy, David E.
AU - Lionikas, Arimantas
AU - Mack, Holly A.
AU - Larsson, Lars
AU - Vogler, George P.
AU - Vandenbergh, David J.
AU - Blizard, David A.
AU - McClearn, Gerald E.
AU - Sharkey, Neil A.
PY - 2009
Y1 - 2009
N2 - Correlations among bone strength, muscle mass, and physical activity suggest that these traits may be modulated by each other and/or by common genetic and/or environmental mechanisms. This study used structural equation modeling (SEM) to explore the extent to which select genetic loci manifest their pleiotropic effects through functional adaptations commonly referred to as Wolff's law. Quantitative trait locus (QTL) analysis was used to identify regions of chromosomes that simultaneously influenced skeletal mechanics, muscle mass, and/or activity-related behaviors in young and aged B6XD2 second-generation (F2) mice of both sexes. SEM was used to further study relationships among select QTLs, bone mechanics, muscle mass, and measures of activity. The SEM approach provided the means to numerically decouple the musculoskeletal effects of mechanical loading from the effects of other physiological processes involved in locomotion and physical activity. It was found that muscle mass was a better predictor of bone mechanics in young females, whereas mechanical loading was a better predictor of bone mechanics in older females. An activity-induced loading factor positively predicted the mechanical behavior of hindlimb bones in older males; contrarily, load-free locomotion (i.e., the remaining effects after removing the effects of loading) negatively predicted bone performance. QTLs on chromosomes 4, 7, and 9 seem to exert some of their influence on bone through actions consistent with Wolff's Law. Further exploration of these and other mechanisms through which genes function will aid in development of individualized interventions able to exploit the numerous complex pathways contributing to skeletal health.
AB - Correlations among bone strength, muscle mass, and physical activity suggest that these traits may be modulated by each other and/or by common genetic and/or environmental mechanisms. This study used structural equation modeling (SEM) to explore the extent to which select genetic loci manifest their pleiotropic effects through functional adaptations commonly referred to as Wolff's law. Quantitative trait locus (QTL) analysis was used to identify regions of chromosomes that simultaneously influenced skeletal mechanics, muscle mass, and/or activity-related behaviors in young and aged B6XD2 second-generation (F2) mice of both sexes. SEM was used to further study relationships among select QTLs, bone mechanics, muscle mass, and measures of activity. The SEM approach provided the means to numerically decouple the musculoskeletal effects of mechanical loading from the effects of other physiological processes involved in locomotion and physical activity. It was found that muscle mass was a better predictor of bone mechanics in young females, whereas mechanical loading was a better predictor of bone mechanics in older females. An activity-induced loading factor positively predicted the mechanical behavior of hindlimb bones in older males; contrarily, load-free locomotion (i.e., the remaining effects after removing the effects of loading) negatively predicted bone performance. QTLs on chromosomes 4, 7, and 9 seem to exert some of their influence on bone through actions consistent with Wolff's Law. Further exploration of these and other mechanisms through which genes function will aid in development of individualized interventions able to exploit the numerous complex pathways contributing to skeletal health.
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U2 - 10.1359/jbmr.090418
DO - 10.1359/jbmr.090418
M3 - Article
C2 - 19419307
AN - SCOPUS:72749109862
SN - 0884-0431
VL - 24
SP - 1608
EP - 1617
JO - Journal of Bone and Mineral Research
JF - Journal of Bone and Mineral Research
IS - 9
ER -