Functional Dissection of the MARK3 GWAS Locus for Bone Mineral Density

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SUMMARY/ABSTRACT Bone mineral density (BMD) is a highly heritable predictor of osteoporotic fracture (ref). Large-scale genome wide association studies (GWAS) have identified dozens of genetic loci harboring variants (SNPs) robustly associated with BMD. These loci constitute a treasure trove of untapped information on novel skeletal regulatory genes and the heritable genomic elements that control their function. However, despite their potential to inform bone biology, the precise causal variants identified by and target genes have not been definitively identified for even a single locus. Using a strategy newly developed to map genes implicated by BMD GWAS onto a bone co- expression network, we predicted causal genes for 30 of 64 GWAS loci. One locus located on chromosome 14q32.32 contained SNPs highly associated with femoral neck BMD (P=5.0 x 10-16) and we predicted that MARK3, one of five genes in the locus, was causal. MARK3 encodes a conserved serine/threonine kinase known to regulate diverse processes including asymmetric cell division, and neuronal differentiation, but its potential role in bone was unknown. Provisional assessment of mice deficient in Mark3 either globally or conditionally (osteoblast) revealed closely similar skeletal phenotypes. Based on these exciting findings, we developed a comprehensive approach to identify the precise causal variant(s) linked to MARK3 and determine how the activity of this kinase in osteoblasts controls bone mass. The studies are divided into three aims: Specific Aim 1: Define the causal genetic mechanism underlying the Chr14q32.32 BMD GWAS locus. Specific Aim 2: Determine how Mark3 functions in bone Specific Aim 3: Test function of the regulatory SNP(s) in vivo. This project was conceived and will be jointly headed by Thomas Clemens at Johns Hopkins University and Charles Farber at the University of Virginia under the auspices of a Multi PI arrangement. The synergy of their complimentary research programs has already been established in previous projects. We strongly believe that the approach will define the biological networks impacted by mutation will contribute substantially to the understanding of their pathology and provide important targets for intervention.