Osteoporosis and other age-associated diseases are proving to have complex etiologies stemming from the fact that most are multifactorial in nature and are largely attributed to the combined effects of many genes and gene-environment interactions. Osteoporosis results in low bone mass and microarchitectural deterioration of bone tissue, especially of trabecular bone. In this work we located quantitative trait loci (QTL) associated with many properties of tibial trabecular bone in two ages of laboratory mice. Interesting trends were evident in the QTL identified at 500 and 800 days of age. Some QTL were found in both age groups. These QTL may prove to be important across the lifespan in building and maintaining bone tissue. Other QTL were only identified at one age point. These may indicate genetic influences that occur at specific times in development. Several loci were identified in both sexes while others appear to be sex-specific.
Through examination of recombinant inbred strains of mice, we have also been able to measure age-related changes in the microarchitecture of trabecular bone and identify QTL related to the age-related changes. Analyzing the QTL specifically related to the changes seen with age has provided several additional sites likely harbouring important genes effecting how bone is lost or gained with age.
Accurate research results of the architecture and density of trabecular bone depend on reliable, consistent data collection. Microcomputed tomography (µCT) has become a valuable and widely available tool that is often used as a dependable replacement for traditional histological measurements of trabecular bone microstructure, but questions still exist about the reproducibility and reliability of data collected using µCT. It was determined that increasing the number of operators involved in data collection increases the variability and reduces the reliability of data collected with µCT and that using methylmethacrylate as an embedding material does not appear to affect the results collected from µCT. We recommend using as few operators as possible to ensure reliable data, ideally with one individual being responsible for all identification of the volume of interest. These findings will inform future study designs leading to better and more reliable data collection.
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