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Bone, Muscle, and Physical Activity: Structural Equation Modeling of Relationships and Genetic Influence With Age
Author(s) -
Lang Dean H,
Conroy David E,
Lionikas Arimantas,
Mack Holly A,
Larsson Lars,
Vogler George P,
Vandenbergh David J,
Blizard David A,
McClearn Gerald E,
Sharkey Neil A
Publication year - 2009
Publication title -
journal of bone and mineral research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.882
H-Index - 241
eISSN - 1523-4681
pISSN - 0884-0431
DOI - 10.1359/jbmr.090418
Subject(s) - quantitative trait locus , structural equation modeling , bone mass , trait , skeletal muscle , biology , anatomy , endocrinology , gene , genetics , osteoporosis , computer science , machine learning , programming language
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 B6×D2 second‐generation (F 2 ) 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.