Osteoarthritis year in review: genetics, genomics, epigenetics

Objective: In this review, we have highlighted advances in genetics, genomics and epigenetics in the field of osteoarthritis (OA) over the past year. Methods: A literature search was performed using PubMed and the criteria: osteoarthritis and one of the following terms genetic(s), genomic(s), epigenetic(s), epigenomic(s), noncoding RNA, microRNA, long noncoding RNA, lncRNA, circular RNA, RNA sequencing, single cell sequencing, or DNA methylation between April 1, 2019 and April 30, 2020. Results: We identified 653 unique publications, many studies spanned multiple search terms. We summarized advances relating to evolutionary genetics, pain, ethnicity specific risk factors, functional studies of gene variants, and interactions between coding and non-coding RNAs in OA pathogenesis. Conclusions: Studies have identified variants contributing to OA susceptibility, candidate biomarkers for diagnosis and prognosis, as well as promising therapeutic candidates. Validation in multiple cohorts, multi-omics strategies, and machine learning aided computational analyses have all contributed to the strength of published literature. Open access data-sets, greater sample sizes to capture broader populations and understanding disease mechanisms by investigating the interactions between multiple tissue types will further aid in progress towards understanding and curing OA. (c) 2020 The Author(s). Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International.

Automated summary

This review highlights recent advances in the genetics, genomics, and epigenetics of osteoarthritis (OA), including identification of variants contributing to OA susceptibility, candidate biomarkers, and potential therapeutic candidates. Multi-omics strategies and machine learning have strengthened the reliability of published literature, while larger sample sizes and open access datasets will be necessary for further progress in understanding and treating OA.