Systems genetics: a novel approach to dissect the genetic basis of osteoporosis

Abstract

From the early 1990s to the middle of the last decade, the search for genes influencing osteoporosis proved difficult with few successes. However, over the last 5 years this has begun to change with the introduction of genome-wide association (GWA) studies. In this short period of time, GWA studies have significantly accelerated the pace of gene discovery, leading to the identification of nearly 100 independent associations for osteoporosis-related traits. However, GWA does not specifically pinpoint causal genes or provide functional context for associations. Thus, there is a need for approaches that provide systems-level insight on how associated variants influence cellular function, downstream gene networks, and ultimately disease. In this review we discuss the emerging field of "systems genetics" and how it is being used in combination with and independent of GWA to improve our understanding of the molecular mechanisms involved in bone fragility.

Figure 1

Systems genetics schema for the investigation of complex osteoporosis-related phenotypes. The approach begins by collecting clinical, global gene expression, and genotype data from family- or population-based samples. QTL or association analysis, depending on the population type, can be used to identify correlations between genotype and clinical/gene expression traits. These data can then be used to prioritize genes based on coincidence between gene expression and clinical QTL or associations and causality modeling. Additionally, network data on highly connected genes or genes belonging to a module correlated with a clinical trait can also be used to screen candidates. High priority genes and pathways can be validated in large populations using association analysis and/or in animal models using transgenic mice. QTL—quantitative trait loci; SNP—single nucleotide polymorphism.