Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies.
Détails
Télécharger: 38049029.pdf (4065.31 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY-NC-ND 4.0
Etat: Public
Version: Final published version
Licence: CC BY-NC-ND 4.0
ID Serval
serval:BIB_D1B4F6D830DD
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies.
Périodique
Osteoarthritis and cartilage
ISSN
1522-9653 (Electronic)
ISSN-L
1063-4584
Statut éditorial
Publié
Date de publication
04/2024
Peer-reviewed
Oui
Volume
32
Numéro
4
Pages
385-397
Langue
anglais
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
Publication Status: ppublish
Résumé
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.
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.
Mots-clé
Humans, Proteomics, Metabolomics, Gene Expression Profiling, Proteome, Osteoarthritis/genetics, Osteoarthritis/metabolism, Multi-omics, Spatial-omics, Transcriptomics
Pubmed
Web of science
Open Access
Oui
Création de la notice
07/12/2023 16:09
Dernière modification de la notice
25/05/2024 6:12