bioRxivBioinformaticsPreprint
JointMap identified SERPINA3+ chondrocytes as a therapeutic target for osteoarthritis
Haoda WuiD, Wenqiang YaniD, M J SuniD, Yifei FaniD, Shaowei JiaiD, Junyan WangiD, Boyang XuiD, Boyun Lu, Yuqing Du, Long CheniD, Jian Yang LiniD, Jin Cheng, Yingfang AoiD, Xiaoqing HuiD
Abstract
BackgroundOsteoarthritis (OA) is a prevalent degenerative joint disease that affects nearly half of the population aged over 65. Recent single-cell transcriptional studies have identified heterogeneous OA-specific chondrocyte subtypes, yet a unified subtype-classification remains incomplete. MethodsIn this study, we integrated a total of 545,946 cells to develop JointMap, an interspecies atlas. The chondrocyte subtypes were analyzed using machine learning algorithms were validated via human samples, animal models, and in vitro cell culture. We performed KAS-seq and analyzed the spatial characters for JointMap. ResultsBased on clinical diagnosis and cross-omic indexes, we identified a novel OA-elevated chondrocyte subtype, SERPINA3+ chondrocytes. Notably, we uncovered their upregulated chondrogenesis function and intercellular communication patterns as potential therapeutic targets. ConclusionsIn summary, JointMap provides a unified framework for the systematic annotation of chondral tissues across species and helps in the identification of druggable networks for articular diseases.
- organism: human
- organism: mouse
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: machine learning (classical)
- Citations
- 0
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