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ABSTRACT: Background
The heterogeneity of osteoarthritis (OA) significantly limits the effectiveness of pharmacological treatments in an unselected patient population. In this context, the identification of OA subtypes is meaningful for the development of therapies that target specific types of OA pathogenesis.Methods
Expression array profiles of 70 OA and 36 control synovial samples were extracted from the GEO database. Unsupervised consensus clustering was performed based on the most variable genes to identify OA subclusters. Next, Joint samples from OA patients were obtained. We divided the OA patient into two subpopulations according to synovial ADCY7 levels. Synovium and cartilage samples from different OA subpopulations were evaluated. In addition, we established a high-fat die
SUBMITTER: Cao X
PROVIDER: S-EPMC8919236 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature