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Ann Rheum Dis. 2019 Jan;78(1):100-110. doi: 10.1136/annrheumdis-2017-212863. Epub 2018 Jul 19.

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

Ji Q#1,2, Zheng Y#2,3,4, Zhang G1, Hu Y2,3,4, Fan X2,3, Hou Y2,3, Wen L2,3, Li L2,3, Xu Y5, Wang Y1, Tang F2,3,4.

Author information

1
Department of Orthopaedics, General Hospital of Chinese People's Liberation Army, Beijing, China.
2
Biomedical Institute for Pioneering Investigation via Convergence and Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China.
3
Beijing Advanced Innovation Center for Genomics (ICG), College of Life Science, Peking University, Beijing, China.
4
Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
5
Department of Traditional Chinese Medicine, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
#
Contributed equally

Abstract

OBJECTIVES:

Understanding 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).

METHODS:

We 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.

RESULTS:

We 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.

CONCLUSIONS:

Our 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.

KEYWORDS:

chondrocytes; knee osteoarthritis; osteoarthritis

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