Evolution and advancements in genomics and epigenomics in OA research: How far we have come.

Details

Serval ID
serval:BIB_107D2E37E60B
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Evolution and advancements in genomics and epigenomics in OA research: How far we have come.
Journal
Osteoarthritis and cartilage
Author(s)
Ramos Y., Rice S.J., Ali S.A., Pastrello C., Jurisica I., Rai M.F., Collins K.H., Lang A., Maerz T., Geurts J., Ruiz-Romero C., June R.K., Thomas Appleton C., Rockel J.S., Kapoor M.
ISSN
1522-9653 (Electronic)
ISSN-L
1063-4584
Publication state
In Press
Peer-reviewed
Oui
Language
english
Notes
Publication types: Journal Article ; Review
Publication Status: aheadofprint
Abstract
Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease.
In this narrative review, we selected articles discussing advancements and application of these technologies to OA biology and pathology. We discuss how genomics, DNA methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients.
Genomics investigations into the genetic links of OA, including using GWAS, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease.
Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.
Keywords
data sharing, epigenomics, genomics, methylomics, miRNomics, osteoarthritis
Pubmed
Create date
08/03/2024 16:57
Last modification date
09/03/2024 8:10
Usage data