QTL analysis of trabecular bone in BXD F₂ and RI mice

A sample of 693 mice was used to identify regions of the mouse genome associated with trabecular bone architecture as measured using αCT. 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. αCT 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 αCT. 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 ≈ 9 of each sex per strain). The proximal tibial metaphyses of the 200-day-old mice were analyzed by μCT 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 F ₂ 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.