The epigenomic landscape of primary tissues in osteoarthritis

OBJECTIVES: Osteoarthritis is a complex joint disease, affecting more than 500 million people worldwide. We investigated DNA methylation profiles and integrated these with matching genotype and transcriptomics data in primary tissues of patients with knee osteoarthritis to enhance our understanding of the regulatory framework that modulates gene expression in osteoarthritis. METHODS: We measured matched genotype and methylation from primary chondrocytes of macroscopically intact (low-grade) and degraded (high-grade) disease cartilage as well as synovium, infrapatellar fat pad, and blood samples, for 314 patients who underwent total knee replacement for osteoarthritis. We generated methylation quantitative trait locus (mQTL) maps in cartilage, synovium, fat pad, and blood, as well as expression quantitative trait methylation (eQTM) maps in cartilage and synovium. We integrated these results with genome-wide association studies (GWAS) to identify likely effector genes of osteoarthritis. RESULTS: We reported widespread associations between genetic variants and methylation as well as between methylation and gene expression. Through colocalisation, we find methylation sites with a potential causal role in osteoarthritis. By tissue-specific integration of colocalisation and eQTM results, we resolved GWAS signals and identified 50 likely effector genes. CONCLUSIONS: We provided the largest genome-wide mQTL maps of low- and high-grade osteoarthritis cartilage and synovium. We further presented the largest cartilage eQTM map for primary cartilage and the first eQTM map in synovium. We found methylation sites with a potential mechanistically causal role in osteoarthritis and associated these with likely effector genes. Together, the presented genome-wide eQTM and mQTL maps constitute relevant resources for osteoarthritis research and beyond.