Bone, Muscle, and Physical Activity: Structural Equation Modeling of Relationships and Genetic Influence With Age

• Published in: Journal of bone and mineral research Vol. 24; no. 9; pp. 1608 - 1617
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: Washington, DC John Wiley and Sons and The American Society for Bone and Mineral Research (ASBMR) 01-09-2009; Wiley; Amer Soc Bone & Mineral Res
• Subjects: Age Factors; Animals; Biological and medical sciences; Biomechanical Phenomena; Bone and Bones - anatomy & histology; bone mechanics; Female; Fundamental and applied biological sciences. Psychology; Male; MEDICIN; MEDICINE; Mice; Mice, Inbred C57BL; Mice, Inbred DBA; Models, Biological; Muscles - anatomy & histology; Organ Size; Original; physical activity; Physical Conditioning, Animal; Quantitative Trait Loci; quantitative trait locus; Skeleton and joints; structural equation modeling; Vertebrates: osteoarticular system, musculoskeletal system; Physical exercise; structural equation modeling; Rodentia; bone mechanics; Striated muscle; Modeling; mice; physical activity; Osteoarticular system; Vertebrata; Mammalia; Mouse; Genetics; quantitative trait locus; Bone; Locus; Age
• ISSN: 0884-0431; 1523-4681; 1523-4681
• DOI: 10.1359/jbmr.090418

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 (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.