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QTL analyses identified several chromosomal regions influencing skeletal phenotypes of the femur and tibia in BXD F 2 and BXD RI populations of mice. QTLs for skeletal traits co-located with each other and with correlated traits such as body weight and length, adipose mass, and serum alkaline phosphatase.Introduction: Past research has shown substantial genetic influence on bone quality, and the impact of reduced bone mass on our aging population has heightened the interest in skeletal genetic research. Materials and Methods: Quantitative trait loci (QTL) analyses were performed on morphologic measures and structural and material properties of the femur and tibia in 200-day-old C57BL/6J × DBA/2 (BXD) F 2 (second filial generation; n ‫ס‬ 400) and BXD recombinant inbred (RI; n ‫ס‬ 23 strains) populations of mice. Body weight, body length, adipose mass, and serum alkaline phosphatase were correlated phenotypes included in the analyses. Results: Skeletal QTLs for morphologic bone measures such as length, width, cortical thickness, and crosssectional area mapped to nearly every chromosome. QTLs for both structural properties (ultimate load, yield load, or stiffness) and material properties (stress and strain characteristics and elastic modulus) mapped to chromosomes 4, 6, 9, 12, 13, 15, and 18. QTLs that were specific to structural properties were identified on chromosomes 1, 2, 3, 7, 8, and 17, and QTLs that were specific to skeletal material properties were identified on chromosomes 5, 11, 16, and 19. QTLs for body size (body weight, body length, and adipose mass) often mapped to the same chromosomal regions as those identified for skeletal traits, suggesting that several QTLs identified as influencing bone could be mediated through body size. Conclusion: New QTLs, not previously reported in the literature, were identified for structural and material properties and morphological measures of the mouse femur and tibia. Body weight and length, adipose mass, and serum alkaline phosphatase were correlated phenotypes that mapped in close proximity of skeletal chromosomal loci. The more specific measures of bone quality included in this investigation enhance our understanding of the functional significance of previously identified QTLs.

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression.Introduction: Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Materials and Methods: Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J × DBA/2 (BXD) second generation (F 2 ) mice (n ‫ס‬ 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. Results and Conclusions:The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted phenotypes. Identifying QTLs that exert their effects on skeletal phenotypes through body size-related pathways as well as those having a more direct and independent influence on bone are equally important in deciphering the complex physiologic pathways responsible for the maintenance of bone health.

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Several QTLs were coincident in males and females although the modest correlation between male and female median lifespans and the identification of sex specific QTLs provide evidence that the genetic architecture underlying longevity in the sexes may differ substantially. The identification of multiple QTLs for longevity will provide valuable resources for both reductionist and integrationist research into mechanisms of life span determination.