Single-cell RNA-seq analysis reveals the progression of human osteoarthritis.
Single-cell RNA-seq analysis reveals the progression of human osteoarthritis.
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单细胞 RNA-seq 分析揭示人类骨关节炎的进展
DOI：
10.1136/annrheumdis-2017-212863
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发表时间：
2019-01
影响因子：
27.4
通讯作者：
Tang F
中科院分区：
文献类型：
--
作者：
Ji Q;Zheng Y;Zhang G;Hu Y;Fan X;Hou Y;Wen L;Li L;Xu Y;Wang Y;Tang F
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.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
4.6
作者：
Li, Yuwei;Ahrens, Molly J.;Dudley, Andrew T.
通讯作者：
Dudley, Andrew T.
影响因子：
14.8
作者：
Islam, Saiful;Kjallquist, Una;Linnarsson, Sten
通讯作者：
Linnarsson, Sten
影响因子：
4.9
作者：
Leijten JC;Bos SD;Landman EB;Georgi N;Jahr H;Meulenbelt I;Post JN;van Blitterswijk CA;Karperien M
通讯作者：
Karperien M
影响因子：
56.9
作者：
Johnson, Kristen;Zhu, Shoutian;Schultz, Peter G.
通讯作者：
Schultz, Peter G.