In women in the US, the annual incidence of osteoporotic fracture is greater than for heart attack, stroke and breast cancer combined. Bone mineral density (BMD) is one of the strongest predictors of fracture risk and studies have demonstrated that up to 80% of the variance can be explained by heritable factors. Many quantitative trait loci (QTL) for BMD have been mapped in mice and humans, but actual gene identification is lacking. The goal of this application is to better identify and map these bone related QTL in mice and to identify some of the underlying candidate genes. The mouse is an excellent model for mapping genes that underlie complex traits, but the effort to find these genes has been hampered by a number of errors in the genetic map used for QTL analysis. A new and corrected mouse genetic map is now available. We have collected the raw data from 18 mouse mapping crosses and will use this new map to recalculate QTL for the bone related traits of BMD, geometry and strength. Then a set of bioinformatic analysis techniques will be systematically applied to bone genetics including meta-analysis, QTL-QTL interaction, combined-cross analysis, comparative genomics and block haplotyping. Based on this bioinformatics analysis, we will then focus on identifying the genes for the most promising QTL. Finding BMD QTL genes could be aided by focusing on one molecular pathway that controls a variety of phenotypes and to use co-mapping of QTL for these phenotypes to narrow the QTL interval. BMD at a young age positively correlated with serum insulin-like growth factor-1 (IGF-1) and negatively correlated with the median lifespan. We will focus on two additional QTL where QTL for these three phenotypes have been co-mapped using both fine mapping crosses and bioinformatics to identify the genes underlying these two QTL. In summary, we will use both advanced genetic analyses and a combined phenotypes approach to better identify candidate genes for BMD.
This research will help us better comprehend what the genes are that control bone mineral density and osteoporosis. Understanding the genetics of osteoporosis will lead to new and better treatments and improve our ability to screen for and prevent this common and debilitating disease.
| Ackert-Bicknell, Cheryl L; Demissie, Serkalem; Tsaih, Shirng-Wern et al. (2012) Genetic variation in TRPS1 may regulate hip geometry as well as bone mineral density. Bone 50:1188-95 |
| Beamer, Wesley G; Shultz, Kathryn L; Coombs 3rd, Harold F et al. (2011) BMD regulation on mouse distal chromosome 1, candidate genes, and response to ovariectomy or dietary fat. J Bone Miner Res 26:88-99 |
| Guan, Yuanfang; Ackert-Bicknell, Cheryl L; Kell, Braden et al. (2010) Functional genomics complements quantitative genetics in identifying disease-gene associations. PLoS Comput Biol 6:e1000991 |
| Ackert-Bicknell, Cheryl L; Karasik, David; Li, Qian et al. (2010) Mouse BMD quantitative trait loci show improved concordance with human genome-wide association loci when recalculated on a new, common mouse genetic map. J Bone Miner Res 25:1808-20 |
