A Chromosome 13 locus is associated with male-specific mortality in mice.

BACKGROUND AND AIM: Mortality is a highly complex trait influenced by a wide array of genetic factors. METHODS: We examined a population of 1200 mice that were F2 generation offspring of a 4-way reciprocal cross between C57BL6/J and DBA2/J strains. Animals were sacrificed at age 200, 500, or 800 days and genotyped at 96 markers. The 800 days old cohort, which were the survivors of a much larger breeding group, were examined for enriched frequency of alleles that benefit survival and depletion of alleles that reduce survival. RESULTS: Loci on Chr 13 in males and on Chr X in females were significantly distorted from Mendelian expectations, even after conservative correction for multiple testing. DBA2/J alleles between 35 and 80 Mb on Chr 13 were underrepresented in the age 800 male animals. D2 genotypes in this region were also associated with premature death during behavioral testing. Furthermore, confirmatory analysis showed BXD recombinant inbred strains carrying the D2 alleles in this region had shorter median survival. Exploration of available pathology data indicated that a syndrome involving dental malocclusions, pancreatic islet hypertrophy, and kidney lipidosis may have mediated the effects of DBA alleles on mortality specifically in male mice. The heterozygote advantage locus on the X Chr was not found to be associated with any pathology. CONCLUSIONS: These results suggest a novel locus influencing survival in the B6/D2 genetic background, perhaps via a metabolic disorder that emerges by 200 days of age in male animals.

Quantitative trait loci (QTL) analysis of longevity in C57BL/6J by DBA/2J (BXD) recombinant inbred mice.

BACKGROUND AND AIMS: Genes associated with longevity have been identified using both single gene and genome-wide approaches in a variety of species. The aim of this study was to identify quantitative trait loci (QTLs) that influence longevity in male and female mice from twenty-three C57BL/6J by DBA/2J (BXD) recombinant inbred (RI) strains. METHODS: Approximately 12 animals of each sex for each RI strain were maintained under standard conditions until natural death or moribundity criteria were met. RESULTS: A number of life span-relevant loci previously reported on chromosomes (Chrs) 7, 8, 10 and 11 were confirmed. In addition, 5 previously unreported QTLs for mouse life span on Chrs 1, 2, 6, 11, and X were identified as significant and 3 QTLs on Chrs 5, 8, and 16 were suggestive. CONCLUSIONS: 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.

Bone, muscle, and physical activity: structural equation modeling of relationships and genetic influence with age.

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 (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.

Genes in context: probing the genetics of fracture resistance.

Fracture resistance is a complex trait dictated by bone volume, shape, internal architecture, and material performance of the calcified tissue itself, all of which may be influenced by a large number of different genetic and environmental processes. Quantitative Trait Loci analyses provide a sobering picture of this system and illustrate the importance of considering genes in context.

QTL analysis of trabecular bone in BXD F2 and RI mice.

UNLABELLED: A sample of 693 mice was used to identify regions of the mouse genome associated with trabecular bone architecture as measured using microCT. QTLs for bone in the proximal tibial metaphysis were identified on several chromosomes indicating regions containing genes that regulate properties of trabecular bone. INTRODUCTION: Age-related osteoporosis is a condition of major concern because of the morbidity and mortality associated with osteoporotic fractures in humans. Osteoporosis is characterized by reduced bone density, strength, and altered trabecular architecture, all of which are quantitative traits resulting from the actions of many genes working in concert with each other and the environment over the lifespan. microCT gives accurate measures of trabecular bone architecture providing phenotypic data related to bone volume and trabecular morphology. The primary objective of this research was to identify chromosomal regions called quantitative trait loci (QTLs) that contain genes influencing trabecular architecture as measured by microCT. MATERIALS AND METHODS: The study used crosses between C57BL/6J (B6) and DBA/2J (D2) as progenitor strains of a second filial (F2) generation (n = 141 males and 148 females) and 23 BXD recombinant inbred (RI) strains (n approximately 9 of each sex per strain). The proximal tibial metaphyses of the 200-day-old mice were analyzed by microCT to assess phenotypic traits characterizing trabecular bone, including bone volume fraction, trabecular connectivity, and quantitative measures of trabecular orientation and anisotropy. Heritabilities were calculated and QTLs were identified using composite interval mapping. RESULTS: A number of phenotypes were found to be highly heritable. Heritability values for measured phenotypes using RI strains ranged from 0.15 for degree of anisotropy in females to 0.51 for connectivity density in females and total volume in males. Significant and confirmed QTLs, with LOD scores 4.3 in the F2 cohort and 1.5 in the corresponding RI cohort were found on chromosomes 1 (43 cM), 5 (44 cM), 6 (20 cM), and 8 (49 cM). Other QTLs with LOD scores ranging from 2.8 to 6.9 in the F2 analyses were found on chromosomes 1, 5, 6, 8, 9, and 12. QTLs were identified using data sets comprised of both male and female quantitative traits, suggesting similar genetic action in both sexes, whereas others seemed to be associated exclusively with one sex or the other, suggesting the possibility of sex-dependent effects. CONCLUSIONS: Identification of the genes underlying these QTLs may lead to improvements in recognizing individuals most at risk for developing osteoporosis and in the design of new therapeutic interventions.

Serum alkaline phosphatase activity is regulated by a chromosomal region containing the alkaline phosphatase 2 gene (Akp2) in C57BL/6J and DBA/2J mice.

Quantitative trait locus (QTL) analyses were conducted to identify chromosomal regions that contribute to variability in serum alkaline phosphatase (AP) enzyme activity in mice derived from the C57BL/6J (B6) and DBA/2J (D2) inbred strains. Serum AP was measured in 400 B6D2 F2 mice at 5 mo and 400 B6D2 F2 mice at 15 mo of age that were genotyped at 96 microsatellite markers, and in 19 BXD recombinant inbred (RI) strains at 5 mo of age. A QTL on the distal end of chromosome 4 was present in all sex- and age-specific analyses with a peak logarithm of odds (LOD) score of 20.36 at 58.51 cM. The Akp2 gene, which encodes the major serum AP isozyme, falls within this QTL region at 70.2 cM where the LOD score reached 13.2 (LOD significance level set at 4.3). Serum AP activity was directly related to the number of D2 alleles of a single nucleotide polymorphism in the 5'-flanking region of the Akp2 gene, although no strain-related differences in hepatic expression of Akp2 RNA were found. A variety of sequence polymorphisms in this chromosomal region could be responsible for the differences in serum AP activity; the Akp2 gene, however, with several known amino acid substitutions between protein sequences of the B6 and D2 strains, is a leading candidate.

Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes.

UNLABELLED: 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 x DBA/2 (BXD) second generation (F(2)) mice (n = 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.

Quantitative trait loci analysis of structural and material skeletal phenotypes in C57BL/6J and DBA/2 second-generation and recombinant inbred mice.

UNLABELLED: QTL analyses identified several chromosomal regions influencing skeletal phenotypes of the femur and tibia in BXD F2 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 x DBA/2 (BXD) F2 (second filial generation; n = 400) and BXD recombinant inbred (RI; n = 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 cross-sectional area mapped to nearly every chromosome. QTLs for both structural properties (ultimate load, yield load, or stiffness) and material properties (stress and straincharacteristics 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.