TY - JOUR
T1 - Three decades of advancements in osteoarthritis research
T2 - insights from transcriptomic, proteomic, and metabolomic studies
AU - Rai, Muhammad Farooq
AU - Collins, Kelsey H.
AU - Lang, Annemarie
AU - Maerz, Tristan
AU - Geurts, Jeroen
AU - Ruiz-Romero, Cristina
AU - June, Ronald K.
AU - Ramos, Yolande
AU - Rice, Sarah J.
AU - Ali, Shabana Amanda
AU - Pastrello, Chiara
AU - Jurisica, Igor
AU - Thomas Appleton, C.
AU - Rockel, Jason S.
AU - Kapoor, Mohit
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023
Y1 - 2023
N2 - Objective: 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. Design: 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. Results: 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. Conclusions: 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.
AB - Objective: 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. Design: 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. Results: 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. Conclusions: 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.
KW - Metabolomics
KW - Multi-omics
KW - Proteomics
KW - Spatial-omics
KW - Transcriptomics
UR - http://www.scopus.com/inward/record.url?scp=85180564124&partnerID=8YFLogxK
U2 - 10.1016/j.joca.2023.11.019
DO - 10.1016/j.joca.2023.11.019
M3 - Article
C2 - 38049029
AN - SCOPUS:85180564124
SN - 1063-4584
JO - Osteoarthritis and Cartilage
JF - Osteoarthritis and Cartilage
ER -