Abstract
The "omnigenic" model of the genetic architecture of complex traits proposed two categories of causal genes: core and peripheral. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. Using a cell-type- and time-point-specific gene co-expression network for mineralizing osteoblasts, we identify a co-expression module enriched for genes implicated by bone mineral density (BMD) genome-wide association studies (GWASs), correlated with invitro osteoblast mineralization and associated with skeletal phenotypes in human monogenic disease and mouse knockouts. Four genes from this module (B4GALNT3, CADM1, DOCK9, and GPR133) are located within the BMD GWAS loci with colocalizing expression quantitative trait loci (eQTL) and exhibit altered BMD in mouse knockouts, suggesting that they are causal genetic drivers of BMD in humans. Our network-based approach identifies a "core" module for BMD and provides a resource for expanding our understanding of the genetics of bone mass.
Highlights
Osteoporosis is a disease characterized by low bone mineral density (BMD) and an increased risk of fracture (Black and Rosen, 2016)
We hypothesized this would allow us to focus on genes with core-like properties in the context of mineralization, a process critical in the regulation of BMD
We began by using weighted gene co-expression network analysis (WGCNA) to construct a co-expression network using transcriptomic profiles generated from mineralizing primary calvarial osteoblasts from 42 strains of Collaborative Cross (CC) mice (Churchill et al, 2004)
Summary
Osteoporosis is a disease characterized by low bone mineral density (BMD) and an increased risk of fracture (Black and Rosen, 2016). During the past decade large-scale genome-wide association studies (GWASs) have begun to dissect the genetics basis of bone traits with a primary focus on BMD (Hsu et al, 2020; Sabik and Farber, 2016). These studies have been tremendously successful, identifying more than 1,100 independent BMD associations (Estrada et al, 2012; Kemp et al, 2017; Morris et al, 2018). Despite the wealth of genetic signals, the genes and mechanisms through which these associations affect bone remain largely unknown (Hsu et al, 2020; Sabik and Farber, 2016)
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