Document Type
Article
Publication Date
10-4-2023
Identifier
DOI: 10.1093/genetics/iyad150; PMCID: PMC10550309
Abstract
There has been a growing interest in the role of the subchondral bone and its resident osteoclasts in the progression of osteoarthritis (OA). A recent genome-wide association study (GWAS) identified 100 independent association signals for OA traits. Most of these signals are led by noncoding variants, suggesting that genetic regulatory effects may drive many of the associations. We have generated a unique human osteoclast-like cell-specific expression quantitative trait locus (eQTL) resource for studying the genetics of bone disease. Considering the potential role of osteoclasts in the pathogenesis of OA, we performed an integrative analysis of this dataset with the recently published OA GWAS results. Summary data-based Mendelian randomization (SMR) and colocalization analyses identified 38 genes with a potential role in OA, including some that have been implicated in Mendelian diseases with joint/skeletal abnormalities, such as BICRA, EIF6, CHST3, and FBN2. Several OA GWAS signals demonstrated colocalization with more than one eQTL peak, including at 19q13.32 (hip OA with BCAM, PRKD2, and BICRA eQTL). We also identified a number of eQTL signals colocalizing with more than one OA trait, including FAM53A, GCAT, HMGN1, MGAT4A, RRP7BP, and TRIOBP. An SMR analysis identified 3 loci with evidence of pleiotropic effects on OA-risk and gene expression: LINC01481, CPNE1, and EIF6. Both CPNE1 and EIF6 are located at 20q11.22, a locus harboring 2 other strong OA candidate genes, GDF5 and UQCC1, suggesting the presence of an OA-risk gene cluster. In summary, we have used our osteoclast-specific eQTL dataset to identify genes potentially involved with the pathogenesis of OA.
Journal Title
Genetics
Volume
225
Issue
2
MeSH Keywords
Humans; Osteoclasts; Genome-Wide Association Study; Genetic Predisposition to Disease; Gene Expression Regulation; Osteoarthritis
Keywords
colocalization; expression quantitative trait locus; gene expression; genome-wide association study; osteoarthritis; osteoclast
Recommended Citation
Mullin BH, Zhu K, Brown SJ, et al. Leveraging osteoclast genetic regulatory data to identify genes with a role in osteoarthritis. Genetics. 2023;225(2):iyad150. doi:10.1093/genetics/iyad150
Comments
This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher's Link: https://doi.org/10.1093/genetics/iyad150