Integrating Genetic and Genomic Analyses to Identify Novel Genes With a Role in the Complex Genetic Architecture of Osteoporosis

Osteoporosis is an increasingly prevalent global health burden characterized by decreased bone strength and increased risk of fracture. Despite its significant impact on human health, there is currently a lack of highly effective treatments free of side effects for osteoporosis. Genetic discovery has been shown to be effective method for the unbiased identification of novel drug targets and genome-wide association studies (GWASs) have begun to provide insight. Over the last decade, osteoporosis-related GWASs have led to the identification of approximately 1100 associations for bone mineral density (BMD) and other bone traits related to risk of fracture. However, there have been limited efforts to identify the causal genes and mechanisms underlying these GWAS associations and there is much left to learn from these studies. Additionally, osteoporosis is influenced not only by the regulation of BMD, but also by gross bone geometry and bone microarchitecture. These parameters are difficult to study using human GWAS, but instead rely on model organism studies, largely in the mouse.
Here, we explore the genetic determinants of osteoporosis, regulating both bone geometry and BMD. We used allele specific expression analysis in inbred mice to identify novel genes potentially influencing bone geometry. Additionally, we built new tools that produce visualizations of the colocalization of expression quantitative trait loci (eQTL) with GWAS associations. Finally, to investigate BMD GWAS, we integrated gene co-expression network analysis with the results of BMD GWAS to identify novel genes influencing BMD. Using both computational and experimental methods, we discovered novel genes influencing osteoporosis and have developed a platform from which we can better understand the mechanisms that underlie bone fragility and increased risk of fracture.