Browse by author
Lookup NU author(s): Dr Sarah RiceORCiD, Kat Cheung, Dr Louise Reynard, Professor John LoughlinORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
OBJECTIVE:Osteoarthritis (OA) is polygenic with over 90 independent genome-wide association loci so far reported. A key next step is the identification of target genes and the molecular mechanisms through which this genetic risk operates. The majority of OA risk-conferring alleles are predicted to act by modulating gene expression. DNA methylation at CpG dinucleotides may be a functional conduit through which this occurs and is detectable by mapping methylation quantitative trait loci, or mQTLs. This approach can therefore provide functional insight into OA risk and will prioritize genes for subsequent investigation. That was our goal, with a focus on the largest set of OA loci yet to be reported.METHOD:We investigated DNA methylation, genotype and RNA sequencing data derived from the cartilage of patients who had undergone arthroplasty and combined this with in silico analyses of expression quantitative trait loci, epigenomes and chromatin interactions.RESULTS:We investigated 42 OA risk loci and in ten of these we identified 24 CpGs in which methylation correlated with genotype (false discovery rate P-values ranging from 0.049 to 1.73x10-25). In silico analyses of these mQTLs prioritised genes and regulatory elements at the majority of the ten loci, with COLGALT2 (encoding a collagen galactosyltransferase), COL11A2 (encoding a polypeptide chain of type XI collagen) and WWP2 (encoding a ubiquitin ligase active during chondrogenesis) emerging as particularly compelling target genes.CONCLUSION:We have highlighted the pivotal role of DNA methylation as a link between genetic risk and OA and prioritized genes for further investigation.
Author(s): Rice SJ, Cheung K, Reynard LN, Loughlin J
Publication type: Article
Publication status: Published
Journal: Osteoarthritis and Cartilage
Year: 2019
Volume: 27
Issue: 10
Pages: 1545-1556
Print publication date: 01/10/2019
Online publication date: 05/06/2019
Acceptance date: 24/05/2019
Date deposited: 10/06/2019
ISSN (print): 1522-9653
ISSN (electronic): 1063-4584
Publisher: Elsevier
URL: https://doi.org/10.1016/j.joca.2019.05.017
DOI: 10.1016/j.joca.2019.05.017
PubMed id: 31173883
Altmetrics provided by Altmetric
