GENETICS OF AGE-SENSITIVE SKELETAL TRAITS IN HETEROGENEOUS MICE

Participants: S. Volkman, C.R. Maynard, S.A. Goldstein, M.R. Moalli, R. Miller, D. T. Burke, A. Galecki, D.C. Kayner, M.W. Stock

Keywords: aging characteristics, genotypic correlations, heterogeneous mice

Introduction

Although it is popularly accepted that genotype influences the onset and degree of age-sensitive traits, this study aims to identify and quantify the contributions of specific alleles within genotyped female heterogeneous (HET) mice. Since age-sensitive traits are expressed within every biological system, this program project incorporates a diversity of disciplines (e.g. immune system, musculature, protein conformations, nervous system, etc.). Our project is designed to evaluate the age-sensitive characteristics of the skeleton -- namely variations in the biomechanical, architectural, and compositional properties of cortical and trabecular bone. We hypothesize that specific variations in these properties will correlate to the specific genotype data and thereby allow for the identification of marker loci that co-segregate with these specific traits. This study is also designed to correlate bone-specific traits with the age-sensitive traits found in the other organ systems. Ultimately, this knowledge could lead to improved capabilities for the prediction and treatment of age-related conditions.

Materials and Methods

The animals used for this study will be 600 genotyped female HET mice bred as the progeny of CB6F1 females and C3D2F1 males. Consequently none of the mice will have identical genotypes, yet each of them will share 50% of their alleles with each of their sisters, having inherited 25% of its genes from each of the four inbred grandparental strains. Statistical analysis will be utilized to identify correlations among genotypes, features of skeletal fragility, and aging characteristics found in the other disciplines.

Both femurs and caudal vertebra #8 will be harvested when the mice are 18 months old. The structural architecture and geometry of one femur and the vertebra will be determined using micro-computed tomography (micro-ct). This information can indicate fragility traits such as reduced bone volume fraction, decreased trabecular strut connectivity, cortical thinning, and/or diminished cross-sectional moment of inertia. The vertebra will then be tested in uniaxial unconfined compression until failure to identify loads and displacements corresponding to yield and failure as well as pre-yield stiffness and the energy absorbed prior to failure. The whole femur will be tested in four-point bending until failure to quantify whole bone mechanical integrity including its ultimate load, yield and ultimate displacements, pre-yield stiffness, and the energy absorbed until failure.

The contralateral femur will be micro-milled into numerous longitudinally-oriented parallelepiped beams (approximately 100 x 100 x 1000 microns) which are subsequently tested in four-point bending to estimate the material properties of the extracellular matrix. Since these micro-beams are subject to considerable variability, at least four micro-beams will be tested from each mouse and their results will be averaged.

The second phase of this study amplifies the statistical power of this model by performing the same series of tests on a population of 180 mice which possess alleles at longevity-associated loci as demonstrated in the first phase. The third phase is the same as the second phase except that the sacrificial ages of the mice will be varied. Consequently we can estimate the influence of these alleles at other time points in the mouse’s life.

Progress

To date, 129 femurs and 55 vertebra have been scanned on the micro-ct system to determine architectural properties. Statistical analysis of the results obtained from the micro-ct analysis revealed a significant batch to batch variation that cannot be explained by random variation alone. A batch is defined here as a group of specimens that was scanned on the same day. Progress is currently being made to alleviate this problem by rescanning a random group of specimens along with a custom phantom. A correction factor will then be available for application to all previous data. To prevent batch to batch variation in the future, the phantom will be scanned on each scanning day and used as a standard by which all other data will be scaled.