Three Decades of Advancements in Osteoarthritis Research: Insights from Transcriptomic, Proteomic, and Metabolomic Studies

dc.contributor.authorFarooq Rai, Muhammad
dc.contributor.authorCollins, Kelsey H.
dc.contributor.authorLang, Annemarie
dc.contributor.authorMaerz, Tristan
dc.contributor.authorGeurts, Jeroen
dc.contributor.authorRuiz-Romero, Cristina
dc.contributor.authorJune, Ronald K.
dc.contributor.authorRamos, Yolande
dc.contributor.authorRice, Sarah J.
dc.contributor.authorAli, Shabana Amanda
dc.contributor.authorPastrello, Chiara
dc.contributor.authorJurisica, Igor
dc.contributor.authorAppleton, C. Thomas
dc.contributor.authorRockel, Jason S.
dc.contributor.authorKapoor, Mohit
dc.date.accessioned2024-02-29T22:49:13Z
dc.date.available2024-02-29T22:49:13Z
dc.date.issued2023-12
dc.description.abstractObjective. 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.en_US
dc.identifier.citationRai, Muhammad Farooq, Kelsey H. Collins, Annemarie Lang, Tristan Maerz, Jeroen Geurts, Cristina Ruiz-Romero, Ronald K. June et al. "Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies." Osteoarthritis and Cartilage (2023).en_US
dc.identifier.issn1063-4584
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/18340
dc.language.isoen_USen_US
dc.publisherElsevier BVen_US
dc.rightscc-by-nc-nden_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectTranscriptomicsen_US
dc.subjectProteomicsen_US
dc.subjectMetabolomicsen_US
dc.subjectSpatial-omicsen_US
dc.subjectMulti-omicsen_US
dc.titleThree Decades of Advancements in Osteoarthritis Research: Insights from Transcriptomic, Proteomic, and Metabolomic Studiesen_US
dc.typeArticleen_US
mus.citation.extentfirstpage1en_US
mus.citation.extentlastpage13en_US
mus.citation.journaltitleOsteoarthritis and Cartilageen_US
mus.data.thumbpage3en_US
mus.identifier.doi10.1016/j.joca.2023.11.019en_US
mus.relation.collegeCollege of Engineeringen_US
mus.relation.departmentMechanical & Industrial Engineering.en_US
mus.relation.universityMontana State University - Bozemanen_US

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