Single-cell RNA-seq analysis reveals the progression of human osteoarthritis

• Published in: Annals of the rheumatic diseases Vol. 78; no. 1; pp. 100 - 110
• Main Authors: Ji, Quanbo, Zheng, Yuxuan, Zhang, Guoqiang, Hu, Yuqiong, Fan, Xiaoying, Hou, Yu, Wen, Lu, Li, Li, Xu, Yameng, Wang, Yan, Tang, Fuchou
• Format: Journal Article
• Language: English
• Published: England Elsevier Limited 01.01.2019; BMJ Publishing Group
• Series: Translational science
• Subjects: Arthritis; Arthroplasty (knee); Cartilage diseases; Cartilage, Articular - cytology; Cell cycle; Chondrocytes; Chondrocytes - metabolism; Chondrogenesis - genetics; Computational Biology; Computer applications; Degeneration; Disease Progression; Gene expression; Gene Expression Profiling; Homeostasis; Humans; Joint surgery; Kinases; Knee; Molecular modelling; Osteoarthritis; Osteoarthritis, Knee - genetics; Pathogenesis; Phenotype; Phenotypes; Progenitor cells; Ribonucleic acid; RNA; Sequence Analysis, RNA; Stem cells; Stem Cells - metabolism; Surgery; Taxonomy; Transcription; Transcriptome; Beijing China; China; knee osteoarthritis; osteoarthritis; chondrocytes
• ISSN: 0003-4967; 1468-2060; 1468-2060
• DOI: 10.1136/annrheumdis-2017-212863

ObjectivesUnderstanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis using single-cell RNA sequencing (scRNA-seq).MethodsWe performed unbiased transcriptome-wide scRNA-seq analysis, computational analysis and histological assays on 1464 chondrocytes from 10 patients with OA undergoing knee arthroplasty surgery. We investigated the relationship between transcriptional programmes of the OA landscape and clinical outcome using severity index and correspondence analysis.ResultsWe identified seven molecularly defined populations of chondrocytes in the human OA cartilage, including three novel phenotypes with distinct functions. We presented gene expression profiles at different OA stages at single-cell resolution. We found a potential transition among proliferative chondrocytes, prehypertrophic chondrocytes and hypertrophic chondrocytes (HTCs) and defined a new subdivision within HTCs. We revealed novel markers for cartilage progenitor cells (CPCs) and demonstrated a relationship between CPCs and fibrocartilage chondrocytes using computational analysis. Notably, we derived predictive targets with respect to clinical outcomes and clarified the role of different cell types for the early diagnosis and treatment of OA.ConclusionsOur results provide new insights into chondrocyte taxonomy and present potential clues for effective and functional manipulation of human OA cartilage regeneration that could lead to improved health.