Unknown

Dataset Information

Identification of osteoarthritis-related genes and potential drugs based on single cell RNA-seq data.


ABSTRACT: Osteoarthritis (OA) is a global problem that seriously affects human health. At present, there is still a lack of effective drugs to treat OA. Therefore, we need to find more drugs with preventive and therapeutic effects on OA. In this study, we obtained single-cell RNA sequencing (scRNA-seq) and bulk-RNA seq datasets from Gene Expression Omnibus (GEO). By using high-dimensional weighted correlation network analysis (hdWGCNA), random forest method and protein-protein interaction (PPI) network analyses, five key genes (CXCL8, CCL20, MMP3, BIRC3 and ICAM1) related to OA were identified and the RT-qPCR experiments verified the differential expression of CXCL8, CCL20 and BIRC3 between Triclocarban (TCC) treated zebrafishes and controls. The SAVERUNNER algorithm predicted 42 candidate drugs. Me

SUBMITTER: Wang N 

PROVIDER: S-EPMC12763847 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature