Dataset Information

Mouse Genome-Wide Association and Systems Genetics Identifies Lipoma HMGIC Fusion Partner (Lhfp) as a Regulator of Bone Mass

ABSTRACT: Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P=3.1 x 10-12) BMD locus on Chromosome 3@52.5 Mbp that replicated in two seperate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts and its expression was regulated by local expression QTL (eQTL) in multiple tissues. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp-/- displayed increased osteogenic differentiation. Lfhp-/- mice also had elevated BMD due to increased cortical bone mass. In conclusion, we used GWAS and systems genetics in mice to identify Lhfp as a regulator of osteoblast activity and bone mass.

ORGANISM(S): Mus musculus

PROVIDER: GSE121887 | GEO | 2018/10/30

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Genome-wide association studies (GWASs) for bone mineral density (BMD), one of the most significant predictors of osteoporotic fracture, have identified over 1100 independent associations; however, few of the causal genes have been identified. Recently, the “omnigenic” model of the genetic architecture of complex traits proposed two general categories of causal genes, core and peripheral. Core genes play a direct role in regulating traits; thus, their identification is key to revealing critical regulators and potential therapeutic targets. Here, we identified a co-expression module enriched for genes exhibiting properties consistent with core genes for BMD by analyzing GWAS data through the lens of a cell-type and timepoint-specific gene co-expression network for mineralizing osteoblasts. We identified multiple co-expression modules enriched for genes implicated by BMD GWAS and prioritized modules based on their enrichment for genes with core-like properties. Only one module, the purple module, was enriched for genes correlated with in vitro mineralization (r = 0.49; FDR = 0.012), with known roles in skeletal development (P <2.2 x 10-16), that when perturbed produce a bone phenotype in mice (OR = 4.1; P = 2.14 x 10-9), and are monogenic bone disease genes in humans (OR=21.3; P=6.94 x 10-9). Furthermore, the purple module contained genes from two distinct transcriptional profiles with regards to osteoblast differentiation, one of which, termed the late differentiation cluster (LDC), was more highly enriched for genes with core-like properties. Within the LDC, we found that the most highly connected genes were more likely to overlap a BMD GWAS association and associations that contained LDC genes overlapped enhancers and promoters in osteoblasts. Finally, we identified four LDC genes (B4GALNT3, CADM1, DOCK9, and GPR133) with colocalizing expression quantitative trait loci (eQTL) and altered BMD in mouse knockouts. Our network-based approach identified a “core” module for BMD and has provided a resource for expanding our understanding of the genetics of bone mass.

Project description:Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits. RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.

Dataset Information

Mouse Genome-Wide Association and Systems Genetics Identifies Lipoma HMGIC Fusion Partner (Lhfp) as a Regulator of Bone Mass

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure