Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies.

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State: Public
Version: Final published version
License: CC BY-NC-ND 4.0
Serval ID
serval:BIB_D1B4F6D830DD
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies.
Journal
Osteoarthritis and cartilage
Author(s)
Rai M.F., Collins K.H., Lang A., Maerz T., Geurts J., Ruiz-Romero C., June R.K., Ramos Y., Rice S.J., Ali S.A., Pastrello C., Jurisica I., Thomas Appleton C., Rockel J.S., Kapoor M.
ISSN
1522-9653 (Electronic)
ISSN-L
1063-4584
Publication state
Published
Issued date
04/2024
Peer-reviewed
Oui
Volume
32
Number
4
Pages
385-397
Language
english
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
Abstract
Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades.
We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease.
Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues.
Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.
Keywords
metabolomics, multi-omics, proteomics, spatial -omics, transcriptomics, Metabolomics, Multi-omics, Proteomics, Spatial-omics, Transcriptomics
Pubmed
Open Access
Yes
Create date
07/12/2023 17:09
Last modification date
03/04/2024 7:18
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